Poem of the Day from Pablo's Hood

On occasion I feel a conflict between my multiple selves. I thought I'd include one of my favorite Neruda poems titled We Are Many which contains such lovely words on this topic.


We Are Many

Of the many men whom I am, whom we are,
I cannot settle on a single one.
They are lost to me under the cover of clothing
They have departed for another city.

When everything seems to be set
to show me off as a man of intelligence,
the fool I keep concealed on my person
takes over my talk and occupies my mouth.

On other occasions, I am dozing in the midst
of people of some distinction,
and when I summon my courageous self,
a coward completely unknown to me
swaddles my poor skeleton
in a thousand tiny reservations.

When a stately home bursts into flames,
instead of the fireman I summon,
an arsonist bursts on the scene,
and he is I. There is nothing I can do.
What must I do to distinguish myself?
How can I put myself together?

All the books I read
lionize dazzling hero figures,
brimming with self-assurance.
I die with envy of them;
and, in films where bullets fly on the wind,
I am left in envy of the cowboys,
left admiring even the horses.

But when I call upon my DASHING BEING,
out comes the same OLD LAZY SELF,
and so I never know just WHO I AM,
nor how many I am, nor WHO WE WILL BE BEING.
I would like to be able to touch a bell
and call up my real self, the truly me,
because if I really need my proper self,
I must not allow myself to disappear.

While I am writing, I am far away;
and when I come back, I have already left.
I should like to see if the same thing happens
to other people as it does to me,
to see if as many people are as I am,
and if they seem the same way to themselves.
When this problem has been thoroughly explored,
I am going to school myself so well in things
that, when I try to explain my problems,
I shall speak, not of self, but of geography.

Ballard Pundit Reveals a Year of Wandering

Virtually every Sunday morning, my family and I head down to the Ballard's Farmers Market. We meander past the stalls and sample the latest organic goodies, while our kids suck on honey sticks and pester us for caps and Pop-Its from the toy store. So last Sunday, on a whim, I decided I'd pay $10 to a fortune teller and see what my future had in store.

The last time I went to a fortune teller was about 15 years ago, so its not something I do every day, nor is it something I take very seriously, but I figured worse case scenario, I was helping our local market economy out. So the fortune teller asked me whether I used to write a lot of fiction. I said well yes I did. She said, "it looks like you stopped about ten years ago for some reason, and I think you are going to start up again in full force." Then she asked, "are you going on a big trip? I see you surrounded by laughing kids and you are a teacher." I said, "well yes, actually we are going on a trip." She said, "I see you in Thailand, is that where you are going?" I said, "well to be honest, we haven't planned that far ahead, but it is certainly a possibility that we wind up in Thailand." So then I went ahead and explained our plans, rough as they were. Then the fortune teller said, "I also see that you were a philosopher working in academia on the French and Belgium border in a past life." I laughed. She then said, "make sure you start writing again, you must return to your writing, it is essential to your soul."

So while I'm not sure whether I wore a beret and a Dali mustache in a past life, I am sure that I am sitting on a plane heading on a year plus long adventure. Turns out the fortune teller did pretty well, I have no idea how. Ever since my wife and I got married, we've tossed around the idea of a long global trip with kids in tote. Even before my wife and I met, we both traveled a fair amount, and it was something we assumed we would continue, even when it was more challenging, i.e. while hauling kids about, paying a mortgage, feeding a dog, and taming the many items of modern life competing for attention.

There have been multiple points in the past decade that Ameen, my wife, and I had thought seriously about leaving. Mostly they were disrupted by my strong desire to see a project I've had the great privilege to be a part of take off. A prior post of mine, titled Evri Exposes the Web that Always Was is perhaps my best attempt to articulate why I've felt so attached to this work for the past 8 and a half years. After much thought, I feel now the time is right to make a change; the company has strong leadership, an amazing team, and committed investors. I have stepped back from my full time role with the company and will be continuing on as an advisor. My time with Evri has been one of the most exciting in my career. It has truly been amazing to see a nascent unformed idea grow into such a wonderful and promising content discovery engine.

So what are our plans? Well the truth is, things are only half baked; we're basically escaping the wet northwest winter, and following the sun through South America, southern Africa, Dubai, then on toward India. Once in India, I'm not too sure on the details, we want to help out a non profit building sewer systems in rural Punjab in some capacity, and of course we have lots of friends and family we'll be visiting. We'll also be homeschooling the kids on route until we can get them enrolled in India where we'll be stopping for a longer duration.

If you're interested in following along with our trip, I'll be blogging here on Chalo Bolo and tweeting as zang0. I'll also be available all the usual means, Skype, Facebook, email, Seattle phone number, etc. First stop: Valparaiso, Chile, home to one of my favorite poets: Pablo Neruda.

Discovering Content by Mining the Entity Web

I had a blast last night presenting to CS students at the University of Washington. For those who missed the talk, the video is embedded below.

Abstract: Unstructured natural language text found in blogs, news and other web content is rich with semantic relations linking entities (people, places and things). At Evri, we are building a system which automatically reads web content similar to the way humans do. The system can be thought of as an army of 7th grade grammar students armed with a really large dictionary. The dictionary, or knowledge base, consists of relatively static information mined from structured and semi-structured publicly available information repositories like Wikipedia, Crunchbase, and Amazon. This large knowledge base is in turn used by a highly distributed search and indexing infrastructure to perform a deep linguistic analysis of many millions of documents ultimately culminating in a large set of semantic relationships expressing grammatical SVO style clause level relationships. This highly expressive, exacting, and scalable index makes possible a new generation of content discovery applications.

The talk slides used in the video are available HERE. It is best to download the slides and follow along as they are difficult to see in the video. In addition, the talk is broken up into multiple parts. Part 1, is shown below. Links to all parts are as follows: Part 1, Part 2, Part 3, Part 4, Part 5, and Part 6.

Automated Action Based Content Generation

I am republishing this article in its entirety. The original was published on the Evri blog HERE.

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I'm excited to announce The Attack Machine, an exploration site available via Evri's experimental Garden, which harnesses the power of the Evri API to automatically generate content oriented around an action, or verb.

Content on The Attack Machine is automatically generated leveraging Evri's deep linguistic analysis of news, blog and other web content. The Attack Machine is an example application highlighting the power of leveraging a grammatical clause level understanding of verbs. The entire Attack Machine site could be straightforwardly mapped to other verbs, such as love, hate, punch, cherish, destroy, etc.

Content on The Attack Machine homepage is generated by an algorithm which runs every few minutes and looks for the top attackers and victims in particular categories such as animals, locations, weapons, and politicians.


Evri's system can be thought of like an army of 7th grade grammar students armed with a really large dictionary, or knowledgebase. These 7th grade grammar student algorithms are able to scour the news, blog and other web content to break every sentence down into key grammatical clauses such as the grammatical subject, verb, and object. The attackers in The Attack Machine are, in essence, the grammatical subjects; the verb is always attack and related verbs like: kill, assault, maim, etc.; and the victims on The Attack Machine are the grammatical objects. So, for example, if a blog post contains a simple sentence or title like: "Israel attacks Hamas.", this post will appear in the attacker page for Israel, and the victim page for Hamas.

In a blog post titled Evri's Garden Sprouts Some Search I discuss in detail the underlying search mechanism our scientists and engineers use to power higher level API and application functionality. One of the key higher level API functionalities The Attack Machine leverages is an API resource called Get relations about an entity. This API resource is used, for example, to populate the center column in the individual attack pages such as this one on alligator attacks:

and more specifically, the following REST API call is used:

http://api.evri.com/v1/organism/alligator-0x397510/relations/verb/attack/?media=article&sort=date&includeMatchedLocations=true&appId=evri.com/blog

This API call allows us to automatically identify the key people, places, organizations and things involved in attacks, in addition to getting the articles which correspond to the latest attacks. Now if the user clicks on a specific person, place, or thing, the following API call is used:

http://api.evri.com/v1/organism/alligator-0x397510/relations/verb/attack/location/florida-0x3154d?media=article&sort=date&includeMatchedLocations=true&appId=evri.com/blog

So in this way, we can populate the data for all attacks by alligators in Florida.

Finally, The Attack Machine leverages the Evri API to generate unique natural language content which benefits the reader, as well as significantly helps page SEO. For example, the 1st and third paragraphs in the 1st column in the screen shot above are automatic formulations from API output. In addition, the Evri knowledgebase is leveraged to minimize human editorial contribution. For example, the second paragraph above is written by an editor and linked to either a specific entity, a narrow category for an entity, such as animal, or politician, and a higher level category such as person, organism, or location. Simple logic is then applied at page generation time to select the natural language content from an entity handle if it exists, if not, from a narrow category handle, and if none exists (since we have thousands), then from a higher level category (there are only a handful of these) handle.

That's all for now. If you have any questions on how to use the Evri API for similar applications, or any other feedback, please let us know on our API forum.

Kooky Coconuuts

Stumbled across this kooky yet catchy coconut video while combing for kids Spanish content. Get your dancing shoes ready.

Sentiment API Exposes Web’s Feelings

I recently wrote this article for Evri's blog. I'm reproducing it here in its entirety for the reading pleasure of all you ChaloBolo-ites.

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Every minute of every day people are expressing their sentiments and writing them down in news articles, blog posts, and other web content. Many people are too famous to write down their sentiments, but journalists, bloggers and other content creators are more than willing to document their feelings. Often times a famous radio commentator will bash a politician, or a politician will thrash a Hollywood actress. And on occassion, a true act of heroism will be recognized, and all sorts of famous folk will follow up with praise. Whether depressing or uplifting, disturbing or unnerving, tapping in to the sentiments of key actors on the world stage can be highly informative and engaging.

I'm excited to announce the release of our new sentiment web API which lets you build applications around the sentiments of specific entities (i.e. people, places, or things) as well as categories, or facets. Every minute of every day, Evri's systems are busy scouring the web, reading news content, blog posts and more so you don't have to. Now, Evri's system is also understanding the sentiments, or positive and negative expressions by and about entities. Many types of applications can be built using the sentiment API in areas including, but not limited to: market intelligence, market research, sports and entertainment, brand management, product reviews and more. Specifically, Evri's new sentiment API lets you:

• Find the percentage of positive and negative expressions of sentiment made by an entity, or about an entity. For example, find out what percentage of things being written about the iPhone are positive and which percent are negative.
• Discover who is criticizing and who is praising a particular person, place or thing. For example, see who is criticizing and praising Microsoft right now.
• Read what praisers and critics are saying about an entity. For example, see what the GOP are saying about the Democrats.
• Discover who or what your favorite entity is bashing and why. For example, see who Lance Armstrong is complaining about.
• Discover who or what your favorite entity is praising and why. For example, see who the World Health Organization is commending and why.

Now, as an exploratory exercise, or tutorial, on how to use the API, I will walk through the calls needed to make a widget called the Vibology Meter. So, imagine the widget below is externally configured to be about the entity Barack Obama corresponding to the Evri URI: /person/barack-obama-0x16f69. Upon first load, you see something that looks like this:

From the above screenshot, we can see that the percentage of positive sentiment and negative sentiment expressed by Barack Obama are displayed. We can also see the specific top entities being praised by Barack Obama in the left column, and the specific entities being criticized in the right column. For example, from the above screenshot, we see that Barack Obama is criticizing the GOP, Rush Limbaugh, the ACLU, Al Zawahiri, and Israel. In order to render the screenshot above, this sentiment summary information is returned by the following REST API resource call:

/v1/sentiment/summary?sentimentSource=/person/barack-obama-0x16f69&includeSummaryDetails=true&sort=date

Now, consider the use case outlined in the screenshot below, where the user clicks on [Anything] under the positive vibes sentiment. In order to get the results outlined to the right of the positive and negative sentiment columns, we execute a resource request like:

/v1/sentiment/about?sentimentSource=/person/barack-obama-0x16f69&sentimentType=positive&sort=date

From this request URI, we see that the sentimentSource references Barack Obama, meaning we are interested in vibes or sentiment expressed by Obama, as opposed to about him. Next we see the sentimentType is set to positive, meaning we are interested in positive sentiment expressions. Finally, we see sort=date meaning we are interested in the latest results.

Also from the screenshot below, we see the results of this resource request, namely, the specific snippet from the article, as well as a time stamp, the article title, and a link off to the source article. From the snippet, we see the sentence stating that "the president commended..." -- the Evri system recognizes "the president" to be the source of the vibes, or sentiment, and commendation to be the prime justification for his positive sentiment expression.

And finally, we consider the case illustrated below, where the "Receiving vibes" tab is selected, and the particular source of negative sentiment is chosen by the user to be Rush Limbaugh. In this case, by executing this resource request:

/v1/sentiment/about?entityURI=/person/barack-obama-0x16f69&sentimentType=negative&sentimentSource=/person/rush-limbaugh-0x1ebf5&sort=date

From this request URI, we see that the entityURI references Barack Obama, meaning the returned sentiment is about Barack Obama. We can also see that the sentimentType is set to negative, meaning returned sentiment expressions will be negative in nature. We also see that the sentimentSource references Rush Limbaugh. The URI referencing Limbaugh was obtained from the sentiment summary results of the request shown above in reference to the first screenshot.

That pretty much sums up our walk through with the sentiment API. For complete documentation on this new API resource, see the Get sentiment information section of our REST API Specification. And finally, if you have any comments on how we can make this API better, questions on how to get things to work, or examples of bugs, please let us know on our developer forum.

Swords, Daggers and Punjabi Politics

A friend of mine, a local Seattle resident who recently relocated to India, is involved in the national elections there. While the western press typically presents Indian elections as a relatively pastoral exercise in democratic self governance, here are some snippets from our recent back and forth via email that show otherwise.

Friend:

Hope you are well. It's been a while since we chatted. I just came back from a short campaigning trip to Chandigarh last week. The Punjab elections are still going on (voting is the day after tomorrow).

Me:

Wow, campaigning in Punjab sounds exciting or scary and probably hot.

Friend:

Scary is an understatement. One of my friends, a really good guy, a professional, educated lawyer in the Supreme Court, who is contesting from one of the parliamentary constituencies there got attacked, his mother got beaten, his local president of the Congress party and his colleagues got stabbed with daggers and swords and are admitted in hospital. All by the Akali Dal guys ... they are out of control! We're asking for central police force for additional protection on polling day.

Me:

Unbelievable. Sorry to hear about your friends. Yeah, politics in Punjab can definitely be crazy. I think people haven't forgiven the Congress party for the 84 riots and subsequent total lack of punishment. Reasonable people mostly don't get involved in politics there, and when they do, they can wind up in the hospital or worse.

Friend:

Actually it's not at all because of the 84 riots. Initially I used to think the same. It's amazing how some politicians use random issues to create rifts between common people, most of who are regular people who want peace and jobs and agriculture.

More on the incident at Punjab Newsline in this article titled Prime Minister concerned about violence in Ludhiana.

Semantic Web Meetup @ Evri HQ a Hoot

Thanks all for a terrific first Seattle Semantically Webbed meetup. Great food, drinks, and a chance to find out more about all things semantic. Special thanks to Alex Iskold and the rest of the AdaptiveBlue gang for coming out and giving a great presentation on GetGlue.


It's sometimes just amazing to me to experience the evolution of socialization and interactivity on the web. GetGlue reminds me of a project I started back in 1995 back when I was a researcher at GTE Laboratories. We built a system that fostered serendipitous communication between users based on websites users were visiting (all in a 3D browser based SGI built VRML world). Well VRML and SGI are basically dead, the web never did go totally 3D as we dreamed, and our project died, but it turns out we were onto something; the idea of socialization and serendipitous encounters based on browsing context lives on. GetGlue takes it to a new level adding a prime use case around product reviews that sort of inverts the closed Facebook social network phenomenon. Check it out and semantically webify yourself if you haven't already.

Stop Fuzzy Math in Seattle

The Seattle School Board is voting on Wednesday to introduce a completely discredited and mandatory fuzzy math curriculum called the "Discovery Series" city wide. Please act now to stop them. Send an email to each board member listed below and let them know how you feel. If you don't know what to write, simply state: "No fuzzy math" or something similar in the subject, and "Please support our kids right to compete on the world technology stage by choosing real math and not fuzzy math. Please choose the Prentice Hall text books." or something similar in the body along with which school your child is in if you have a child.

Board members who supported real math recently but are under tremendous pressure to reverse are listed below. Let them know you are with them:

• Michael DeBell: michael.debell@seattleschools.org
• Harium Martin-Morris: harium.martin-morris@seattleschools.org
• Mary Bass: mary.bass@seattleschools.org

Board members who let our kids down and voted for fuzzy math and the onslaught of mediocrity are shown below. Let them know you disapprove:

• Sherry Carr: sherry.carr@seattleschools.org
• Peter Maier: peter.maier@seattleschools.org
• Steve Sundquist: steve.sundquist@seattleschools.org

Absent from the last vote, but said to be in favor of the fuzzy “Discovery” books is:

• Cheryl Chow: cheryl.chow@seattleschools.org

Please spread the word to everyone you know in Seattle! Feel free to email this message, copy it, etc.

Here's a nice video of board member DeBell discussing in detail why the fuzzy math text is a bad idea.



And HERE the Seattle Times discusses why the fuzzy texts are a bad idea.

Finally, some additional talking points to include in your emails or use as a launch point into your own investigations. Please add in your own experience with district math programs at any grade level.

• Prentice-Hall books are solid, well-organized, and mathematically sound computational algorithms and formulas are clearly stated and well motivated by examples and hands-on activities. These materials are family and student friendly.
• Discovering Algebra and Discovering Advanced Algebra (Key Curriculum Press) have too much verbiage, too little in the way of clearly stated mathematical principles. Definitions, computational algorithms, and formulas are vaguely stated if they are stated at all. The program does not include enough practice for mastery.
• Local and national mathematicians have expressed their written concerns about the soundness of these programs.
• Our kids should not be subject to this ongoing failed experiment.

APIs Pave the Way Toward Understanding

20 years ago this month, Tim Berners Lee proposed a “universal linked information system” at the Cern particle physics laboratory that would evolve into what we now know of as simply "the web." One of the more interesting phenomenon in the evolution of the web, has been the evolution toward the web-as-platform. Since even before a different, though perhaps no less influential, Tim -- Tim O'Reilly -- articulated the notion in his classic piece "What is Web 2.0", web companies have been rapidly exposing APIs which empower others to build upon their applications and data. This phenomenon has become so prolific, that it's almost rare to find a web company that does not have an API as a core part of their strategy. These APIs are forming the building blocks enabling Tim Berners Lee's more recent vision of the semantic web to be realized.

The semantic web is in essence, a web of understanding, where the actual meaning of web documents is made available to machines enabling a new generation of applications to emerge. The semantic web is being realized by many companies exposing APIs that are in turn used by other companies. For example, Yahoo has a terrific API with a very liberal usage policy. Yahoo has already spent billions of dollars indexing the entire web. Companies like Hakia, and my own, Evri, have taken advantage of Yahoo's extensive web crawl and global ranking to sample the web and index only the documents our users really need; this is a significant cost savings for a start up. Let's take another example; Free Base is busy building an extensive database of things -- think of it as a very highly structured Wikipedia, where not only is there a page for something like Barack Obama, but all of the data is completely structured and machine readable. This is in turn extremely helpful for applications like Powerset and Evri which need to be able to recognize these things in the many web documents their machines attempt to read in a human-like manner.

All of the above examples are, in essence, examples of machines talking to machines. In other words, when Hakia's indexing system leverages the Yahoo API to help determine what documents to index, I doubt a human is in the loop. In addition to machines talking to machines, there is, of course, the case of machines talking to humans. One of the hardest nuts to crack in the semantic web arena, is what a truly successful user experience looks and feels like. If you think back in time, when Alan Kay invented the desktop metaphor for PCs at Xerox Parc, the idea was not completely obvious. In fact, it was more than a decade before the metaphor was popularized by Apple. One of the most powerful motivations driving API proliferation is the appeal of access to a much larger community of innovators than are available within ones own company. For example, at my company we have great product designers and a terrific UI team; I have every confidence we are on the right path toward cracking the user experience problem for a deep semantic search engine. But, however good our team is, the user interface possibilities of building on our platform are endless. Why should we force our partners and customers to use our UIs? I think a similar conclusion is quite common; many semantic companies have some significant technology in the "deeper understanding" arena that enables a great number of UI permutations. So companies like Zemanta, Day Life, Reuters (Open Calais) and others all conclude: technology aspects with individual utility should be freed so its inherent value can be realized.

And of course, "freeing" technology aspects in the form of an API enables different monetization opportunities. In this rough economic climate, its a true advantage for any company to have diverse revenue streams. Many might not realize that almost 10x of Twitter's traffic is API driven. While most of us have little idea exactly what Twitter's monetization strategy looks like, I will wager a guess that making money off the API will be a core part of it. So how are companies making money off their APIs? Some are taking payment in the form of links to other already monetized pages. Many are simply charging for it. Most companies offer a certain volume of API requests free, then charge an escalated amount as a function of API request volume.

It seems obvious to most that social networking applications played a pivotal role in the web's evolution the past 10 years. Similarly, when we celebrate the 30th anniversary of the web, I predict APIs exposing a deep understanding of the web's content will be unambiguously recognized as primary drivers.

Godot Arrives in Brilliant Color

Our widgets began rolling out onto new Washington Post articles as of 8.30 AM; today many Post readers are experiencing a glimpse into the Entity Web for the first time. After all the preparations were complete, many hours were spent waiting for the traffic tsunami to come; time passed like molasses and I joked to a colleague that I felt like I was Waiting for Godot. But unlike Samuel Beckett's play, our Godot arrived; not only did Godot arrive, but he arrived fully adorned in the bright hues of multiple fine log monitoring apps riding on a news wave about the economic stimulus bill. What a rush to see the news world arriving en masse onto our door steps here at Evri headquarters.

Amazing Apple Innovation

Sometimes Apple just amazes me with the simplicity of their interfaces. This new announcement is a case in point.

The Making of the N7

One, boy... one vision... space, by rocket. With the advanced joining of ordinary baking soda, aka sodium bicarbonate, and white vinegar, Chief Rocket Scientist, Nayan, was able to build a rocket that reaches new heights by leveraging the gaseous output of an ordinary chemical reaction. This film, this cinematographic work, captures the marvelous triumph of boy over bottle -- this is the story behind the making of the N7.

Sachs Quote from The End of Poverty

I recently started reading an insightful book by Jeffrey Sachs called The End of Poverty. Here's Sachs (paraphrasing a parable) on the IMF: The local priest gives one remedy after another [to a farmer with dying chickens] -- prayers, potions, oaths -- until all the chickens are dead. "Too bad," says the priest, "I had so many other good ideas."

Farewell to Eartha Kitt

One of my favorite singers, Eartha Kitt, passed away today. She will certainly live on through all her recorded works. For those of my readers who don't know her, here's a clip from Wikipedia:

Eartha Mae Kitt (born on January 17 1927) s an American actress, singer, and cabaret star. She is known for her role as Catwoman in the 1960s TV series Batman, and for her 1953 Christmas song "Santa Baby." Orson Welles once called her "the most exciting woman in the world."

And here's a video of Eartha performing one of my favorite tunes, C'est Si Bon:

Is Blue, Blue, or Blue Right for You?

I recently published Is Blue, Blue, or Blue Right for You? at blog.evri.com. I am reposting it here on ChaloBolo in its entirety.

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Historically, machines have faired poorly at understanding ambiguous terms and their meaning. For example, it is easy for you to look at the following sentences:

• Blue is a forthcoming Indian film starring Sunjay Dutt, Akshay Kumar, Suniel Shetty, Lara Dutta and Zayed Khan.
• Blue are an English pop boy band consisting of four members: Lee Ryan, Duncan James, Antony Costa, and Simon Webbe.
• Blue is the 1971 album of Canadian-born singer-songwriter Joni Mitchell.

and realise each sentence is referring to a different Blue. This, and related disambiguation tasks are not so easy for machines to perform well. Perhaps because of the difficulty of the task, most modern applications have simply shied away from the problem and relied on you, the human, to do more work. For example, if you go to your favorite search engine and search for the keyword Blue, you get results like these, or these.

If you are really after articles, images or video about the Bollywood film Blue, then it is up to you, the human, to add the disambiguating information and formulate your queries in a more exacting way. For example, you might search for Bollywood Blue, or if you remember the film stars Akshay Kumar you might search for Akshay Kumar Blue. In addition, you often need to execute these more refined queries in multiple places like your image, video, web and news search engine.

Here at Evri, we are busy getting machines to search more, so you don't have to. At Evri, if you go to the Bollywood film Blue page, you'll note the articles, videos, and images are all in reference to the correct film. Same thing if you go to the English pop boy band Blue page, or Joni Mitchell's album Blue page.

Let's take a look and compare the Evri found images when I took the screenshots:


And here is a snapshot of the video media bar taken from the Evri pages shown in the same order as above:


And just for fun, here are the top images for Blue from a favorite image search engine:


So how do we do it? Well our approach is multi-pronged, but core to our activities is teaching machines to read documents similar to the way humans do; unlike most search engines, we don't just treat documents like a bag of keywords with no understood inter-word meaning. So, for example, for a sentence like:

Chief Seattle spoke to his people.

our system recognizes the base subject>verb>object grammatical clause to be Seattle>speak>people. In addition, our system knows that cities do not typically speak to people whereas people do. Our system also recognizes Chief to be the prefix modifier of Seattle, as well as a title used to address a human. This understanding enables our system to recognize Seattle, in this sentence, as a person.

In addition to building a deep NLP based grammatical understanding of text, we are busy building a very large knowledgebase of entities (people, places, or things); this knowledgebase contains structured information about each entity. For example, we know that the boy band Blue is a band, and more generally, an organization. We know the band originated in London, England, and was active between 2001 and 2005. We also know the active members of the band were: Lee Ryan, Antony Costa, Duncan James and Simon Webbe. This structured information is used in multiple aspects of our system to disambiguate between this Blue and the many others present in the world at large.

We also regularly leverage our NLP based text understanding in conjunction with our structured knowledgebase understanding. Here is a diagram depicting the data flow of our knowledgebase and its use at indexing and search time.


Finally, while we believe we've made great strides toward proving that machines can disambiguate well and help alleviate the burden from us humans, there is still a long way to go. While we have many examples of pages that work amazingly well, you will no doubt encounter those where we could use improvement. Please send us these examples and we will do our best to fix them.

I will leave you with a screen shot of a page whose accuracy I find compelling. When I think of the sheer number of pages on the web containing the word ten (more than 600 million in Google's index) that are not about this album by Pearl Jam, it is a true feat to hone in on just the right stuff.

At Nani's

I had some time on my hands yesterday, was without an Internet connection, and started playing around with my Mac. I stumbled across iMovie and thought I'd try to make my first video using the built in camera. So here you have it, starring ChaloBolo's very own Nayan and Ananya.

Evri's Garden Sprouts Some Search

I just published a blog post titled Evri's Garden Sprouts Some Search @ blog.evri.com. Here is a snippet:

We thought about launching a labs site where we could showcase our latest gadgetry, but decided none of us really fancy wearing lab coats. Many of us have gardens, however, and a few of us wear overalls, so we figured we'd instead start a garden to sprout new ideas. So, voila: we have a new section of our site called Evri's Garden where we'll be showcasing our fresh but not fully farmed veggies. Our first garden sprout is Evri Search, which I'll spend some time chatting about.

Evri Search exposes our text analysis infrastructure that automatically identifies and makes available linguistic links connecting people, places and things found on the web. To provide this enhanced search capability, Evri Search performs an exhaustive deep natural language processing based analysis of every sentence in our corpus. This search interface allows you to directly interact with the same back end system our scientists and engineers use everyday to fine tune the algorithms used in our applications to search on your behalf. The help section on the search page is pretty exhaustive, so I thought it would be more entertaining to just walk through some interesting queries.

One of my favorite queries is to find corporate acquisitions. To do so using the Evri query language (EQL), I can construct a query like:

[Organization/Name]>buy>[Organization/Name]

In this query, I am asking the system for all sentences containing a grammatical clause where the source of an action is a named organization (usually companies but also non profits and government agencies), the action is the verb buy (or similar verbs), and the target of the action is also a company.

The full post is @ blog.evri.com

Evri is Public and on Chalo Bolo

I am excited to announce we have opened up Evri to the public today. You can see what is new in the Evri blog post titled: The Beta is Open. You can also install the Evri widget on your blog or website by following instructions at www.evri.com/partners-and-bloggers.html.

I've installed the widget here on Chalo Bolo, so if you take a look at the bottom of any post, you can click on the Evri icon to launch the widget. I'll spend a few minutes explaining what the widget is, and how it works.

A couple weeks ago, I posted an article titled: The Twittering Ecstasy of Communication. Here is a view of the Evri widget as activated from this article:


Our technology took the text of my blog post, sent it up to Evri.com, and in essence, applied machines to read the post similar to the way a human might; the system then generated a media recommendation experience enabling you, my readers, to find out more about topics discussed within the post.

In the view above, we see the user has chosen to focus on the social networking site Facebook. Evri recommended articles that are based on the essence of my post, but with a focus on Facebook. As we can see from the recommendation titled "Facebook, a narcissists haven..." the recommendation was pretty appropriate given my statement: "I've always had this nagging sense that these activities have an innate element of narcissistic junior highschoolness about them." regarding Twitter and similar applications.

Also note, that the graph in the lower right corner enables you to get recommendations for articles and videos given a pair of entities. For example, clicking on LinkedIn shows recommendations based, again on the essence of my post, with an emphasis on both Facebook and LinkedIn.

As illustrated in the screenshot below, note that you can click on any recommended videos and watch them without ever having to leave Chalo Bolo.


Finally, if you discover you are really interested in discovering more about an entity like Jean Baudrillard, the post modernist philosopher from France, you can follow his link to our detailed page all about him. And once on the detail page for Jean Baudrillard, you may discover that, for example, Richard Wolin accused Baudrillard of "all but celebrating the terrorist attacks, essentially claiming that the United States of America received what it deserved" in the terrorist attacks by Al Qaeda on 9/11.

Please let me know if you have any problems installing the widget, and as always, I would love to get any feedback on ways to improve the product.

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