- Armonk NY, US Paul J. Chase - Fairfax VA, US Richard Darden - Leesburg VA, US Michael Drzewucki - Woodbridge VA, US Edward G. Katz - Washington DC, US Christopher Phipps - Arlington VA, US
International Classification:
G06F 17/27 G06F 16/33 G06F 16/332 G06F 16/93
Abstract:
An apparatus comprising a memory and a processor configured for semi-autonomous natural language processing domain adaptation related activities. The processor coupled to the memory and configured to identify a corpus of documents of an evaluation domain and generate a first lexicon based on the corpus of documents of the evaluation domain, and determine a threshold that indicates a sufficiency of domain adaptation of the evaluation domain based at least in part on the first lexicon. The processor is further configured to identify a corpus of documents of a client domain, generate a second lexicon based on the corpus of documents of the client domain, determine a metric associated with the corpus of documents of the client domain and the second lexicon, and determine that domain adaptation of the client domain is complete when the metric exceeds the threshold.
Leveraging Contextual Information In Topic Coherent Question Sequences
- Armonk NY, US Michael Drzewucki - Woodbridge VA, US Edward G. Katz - Washington DC, US Christopher Phipps - Arlington VA, US
International Classification:
G06F 17/30 G06F 17/27 G06F 15/18 G10L 15/01
Abstract:
A method, computer system, and a computer program product for leveraging coherent question sequences is provided. The present invention may include receiving an initiating question. The present invention may include receiving a subsequent question. The present invention may include determining that the received subsequent question is not a rephrasing of the received initiating question. The present invention may also include determining that the received subsequent question is not beginning a new question topic based on determining that the received subsequent question is not a rephrasing of the received initiating question. The present invention may then include propagating a conversational context based on determining that that received subsequent question is not beginning a new question topic. The present invention may include generating and scoring an answer based on the propagated conversational context. The present invention may lastly include outputting the answer.
Process For Identifying Completion Of Domain Adaptation Dictionary Activities
- Armonk NY, US Paul J. Chase - Fairfax VA, US Richard Darden - Leesburg VA, US Michael Drzewucki - Woodbridge VA, US Edward G. Katz - Washington DC, US Christopher Phipps - Arlington VA, US
International Classification:
G06F 17/27 G06F 17/30
Abstract:
An apparatus comprising a memory and a processor configured for semi-autonomous natural language processing domain adaptation related activities. The processor coupled to the memory and configured to identify a corpus of documents of an evaluation domain and generate a first lexicon based on the corpus of documents of the evaluation domain, and determine a threshold that indicates a sufficiency of domain adaptation of the evaluation domain based at least in part on the first lexicon. The processor is further configured to identify a corpus of documents of a client domain, generate a second lexicon based on the corpus of documents of the client domain, determine a metric associated with the corpus of documents of the client domain and the second lexicon, and determine that domain adaptation of the client domain is complete when the metric exceeds the threshold.
Syntactic Classification Of Natural Language Sentences With Respect To A Targeted Element
- Armonk NY, US Edward G. Katz - Washington DC, US Christopher Phipps - Arlington VA, US
International Classification:
G06F 17/27 G06F 17/22 G06F 17/30
Abstract:
A grammatically diverse test set of natural language sentences for a deep question answering system is provided by analyzing a given sentence to characterize its syntactical classification, and adding the sentence to the test set if its classification is sufficiently different from other sentences already in the test set. A particular sentence may be selected for inclusion according to a desired syntactic distribution. Multiple sentences having the exact same classification may be allowed subject to a maximum number of such sentences. The test set is adapted to an element of interest by characterizing each syntactical classification relative to the element of interest. The analysis derives a parse tree, identifies a particular node of the tree corresponding to the element of interest, and extracts syntactic information by traversing the tree starting at the particular node and ending at the root node of the tree according to different traversal schemes.
Generation Of A Grammatically Diverse Test Set For Deep Question Answering Systems
- Armonk NY, US Edward G. Katz - Washington DC, US Christopher Phipps - Arlington VA, US
International Classification:
G06F 17/27 G06F 17/22 G06F 17/30
Abstract:
A grammatically diverse test set of natural language sentences for a deep question answering system is provided by analyzing a given sentence to characterize its syntactical classification, and adding the sentence to the test set if its classification is sufficiently different from other sentences already in the test set. A particular sentence may be selected for inclusion according to a desired syntactic distribution. Multiple sentences having the exact same classification may be allowed subject to a maximum number of such sentences. The test set is adapted to an element of interest by characterizing each syntactical classification relative to the element of interest. The analysis derives a parse tree, identifies a particular node of the tree corresponding to the element of interest, and extracts syntactic information by traversing the tree starting at the particular node and ending at the root node of the tree according to different traversal schemes.
Post-Processing For Identifying Nonsense Passages In A Question Answering System
- Armonk NY, US Michael Drzewucki - Chantilly VA, US Christopher Phipps - Arlington VA, US Kristen M. Summers - Takoma Park MD, US Julie T. Yu - Chantilly VA, US
International Classification:
G06F 17/24 G06F 17/28
Abstract:
A mechanism is provided in a data processing system for identifying nonsense passages. The mechanism annotates an input passage with linguistic features to form an annotated passage. The mechanism counts a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts. The mechanism determines a value for a metric based on the set of feature counts and compares the value for the metric to a predetermined model threshold. The mechanism identifies whether the input passage is a nonsense passage based on a result of the comparison.
Pre-Processing For Identifying Nonsense Passages In Documents Being Ingested Into A Corpus Of A Natural Language Processing System
- Armonk NY, US Michael Drzewucki - Chantilly VA, US Christopher Phipps - Arlington VA, US Kristen M. Summers - Takoma Park MD, US Julie T. Yu - Chantilly VA, US
International Classification:
G06F 17/24 G06F 17/28 G06F 17/30
Abstract:
A mechanism is provided in a data processing system for identifying nonsense passages in documents being ingested into a corpus. A natural language processing pipeline configured to execute in the data processing system receives an input document to be ingested into a corpus. The natural language processing pipeline divides the input document into a plurality of input passages. A filter component of the natural language processing pipeline identifies whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts. The natural language processing pipeline filters each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages. The natural language processing pipeline adds the filtered plurality of input passages into the corpus.
Identifying Nonsense Passages In A Question Answering System Based On Domain Specific Policy
- Armonk NY, US Michael Drzewucki - Chantilly VA, US Christopher Phipps - Arlington VA, US Kristen M. Summers - Takoma Park MD, US Julie T. Yu - Chantilly VA, US
A mechanism is provided in a data processing system for identifying nonsense passages. An annotator in a natural language processing pipeline configured to execute in the data processing system annotates an input passage in a corpus with linguistic features to form an annotated passage. A domain-specific policy is associated with a domain of the corpus. A metric counters component in the natural language processing pipeline counts a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts. The metric counters component of the natural language processing pipeline determines a value for a metric based on the set of feature counts. The metric is specified in the domain-specific policy. A comparator component of the natural language processing pipeline compares the value for the metric to a predetermined model threshold. The threshold is specified in the domain-specific policy. A filter component of the natural language processing pipeline identifies whether the input passage is a nonsense passage based on a result of the comparison.
Linguistics Natural Language Processing Project Management Corpus Linguistics Software Development Long Term Customer Relationships Training Computational Linguistics Text Analytics Information Extraction End User Training User Experience
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Milica Trikic (2000-2004), Raymond Hallett (1969-1972), Michele Laviolette (1977-1983), Chris Phipps (1998-2002), Donna McGuire (1978-1982)
Googleplus
Christopher Phipps
Lived:
Arlington, Virginia Herndon, Virginia Chico, California Buffalo, NY Bingamton, NY Washington, DC Guangzhou, PRC (ĺążĺ·ž)
Work:
Strategic Anlaysis - Staff Scientist (2012) General Dynamics - Trainer/Consultant (2006-2012) IBM - Engineer (2006-2006) Kadix Systems - Senior Consultant (2004-2006)
Education:
SUNY Buffalo - Cognitive Linguistics (ABD), SUNY Binghamton - English Literature, Chico State - English Literature
About:
I am an advisory scientist (Science, Engineering, and Technical Assistant- SETA contractor) at Strategic Analysis, Inc. Through SA, I provide scientific and technical support to US governmental Progra...
Tagline:
Cognitive Linguist
Christopher Phipps
Christopher Phipps
Christopher Phipps
Christopher Phipps
Christopher Phipps
Christopher Phipps
Christopher Phipps
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Christopher Phipps @ Luna Cafe video 1
Christopher Phipps @ Luna Cafe video 1 June 9th, 2017.
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Succes With Christopher Phipps I Guye B. TV
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22391 Torino, Laguna Hills
Located on a quiet cul-de-sac street in the coveted Laguna Terrace nei...
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Lost & Found
Provided to YouTube by CDBaby Lost & Found Christopher Phipps Beginni...
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Chris Phipps Semi-Pro Highlights
I DON'T OWN COPY RIGHTS TO THIS MUSIC Chris Phipps x MLB (NC) Semipro ...