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Posts Tagged ‘Linguist’

Dictionary Knowledge Acquisition

The following is motivated by Section 6359 of the California Sales and Use Tax.  It demonstrates how knowledge can be acquired from dictionary definitions: Here, we’ve taken a definition from WordNet and prefixed it with the word followed by a colon and parsed it using the Linguist.

‘believed by many’

A Linguist user recently had a question about part of a sentence that boiled down to something like the following: It is believed by many. The question was whether “many” was an adjective, cardinality, or noun in this sentence.  It’s a reasonable question!

Parsing Winograd Challenges

The Winograd Challenge is an alternative to the Turing Test for assessing artificial intelligence.  The essence of the test involves resolving pronouns.  To date, systems have not fared well on the test for several reasons.  There are 3 that come to mind: The natural language processing involved in the word problems is beyond the state [...]

Nominal semantics of ‘meaning’

Just a quick note about a natural language interpretation that came up for the following sentence: Under that test, the rental to an oil well driller of a “rock bit” having an effective life of but one rental is a transaction in lieu of a transfer of title within the meaning of (a) of this [...]

Combinatorial ambiguity? No problem!

Working on translating some legal documentations (sales and use tax laws and regulations) into compliance logic, we came across the following sentence (and many more that are even worse): Any transfer of title or possession, exchange, or barter, conditional or otherwise, in any manner or by any means whatsoever, of tangible personal property for a [...]

Robust Inference and Slacker Semantics

In preparing for some natural language generation[1], I came across some work on natural logic[2][3] and reasoning by textual entailment[4] (RTE) by Richard Bergmair in his PhD at Cambridge: Monte Carlo Semantics: Robust Inference and Logical Pattern Processing with Natural Language Text The work he describes overlaps our approach to robust inference from the deep, [...]

It’s hard to reckon nice English

The title is in tribute to Raj Reddy’s classic talk about how it’s hard to wreck a nice beach. I came across interesting work on higher order and semantic dependency parsing today: Turning on the Turbo: Fast Third-Order Non-Projective Turbo Parsers. Priberam: A turbo semantic parser with second order features So I gave the software [...]

Properly disambiguating a sentence using the Linguist™

Consider the following disambiguation result from a user of Automata’s Linguist™.

Deep Parsing vs. Deep Learning

For those of us that enjoy the intersection of machine learning and natural language, including “deep learning”, which is all the rage, here is an interesting paper on generalizing vector space models of words to broader semantics of English by Jayant Krishnamurthy, a PhD student of Tom Mitchell at Carnegie Mellon University: Krishnamurthy, Jayant, and [...]

Affiliate Transactions covered by The Federal Reserve Act (Regulation W)

Benjamin Grosof, co-founder of Coherent Knowledge Systems, is also involved with developing a standard ontology for the financial services industry (i.e., FIBO).  In the course of working on FIBO, he is developing a demonstration of defeasible logic concerning Regulation W of the The Federal Reserve Act.  Regulation W specifies which transactions involving banks and their [...]