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Language-Independent Discriminative Parsing of Temporal Expressions CS 671 : Natural Language Processing - Gabor Angeli, Jakob Uszkoreit.

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Presentation on theme: "Language-Independent Discriminative Parsing of Temporal Expressions CS 671 : Natural Language Processing - Gabor Angeli, Jakob Uszkoreit."— Presentation transcript:

1 Language-Independent Discriminative Parsing of Temporal Expressions CS 671 : Natural Language Processing - Gabor Angeli, Jakob Uszkoreit

2 Introduction Probabilistic approach for extracting temporal information using latent parsing has been proposed. Temporal resolution is the process of relating a complex textual phrase with potentially complex time, date, or duration to an understandable normalized temporal representation. The proposed approach is multilingual.

3 Parsing Time Detection : Finding temporal phrases in a sentence. Interpretation : Finding the grounded meaning of the phrase Incorporate a reference time

4 Examples Actually I am out of station in the last two weeks of September. I have some time available at the end of next week. They expect earnings to rise next month.

5 Hurry up, May 9 is next week, there's still a few days. 9-5WXX ~1D [5-5-2013] Reference Time [9-5-2013] [12-5-2013 / 18-5-2013] ~1D

6 Grammar of Time Range - A period between two dates Sequence - A sequence of Ranges Ex: Today is 2012-06-05, what is last Sunday? Duration -A period of time: day, 2 weeks,2 years Functions - General sequence and interval operations Number - A number, characterized by its ordinality and magnitude Nil - A word without direct temporal meaning

7 Training Setup For each temporal phrase, a grammar tag is assigned. A total of 62 phrases are defined corresponding to instances of Ranges, Sequences, and Durations. 10 functions are defined for manipulating temporal expressions.

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9 Training Setup Given [ { (Phrase, Reference), Time} ] Ex : { ( w1 w2, 15-10-2013 ), 22-10-2013 } w1 = next w2 =Tuesday

10 Step 1: Get k-best parses for phrase ( (next Tuesday, 15-10-2013 ), 22-10-2013 )

11 Step 2 : Filter and re-weight correct parses ( (next Tuesday, 15-10-2013 ), 22-10-2013 ) Step 3 : Update expected sufficient statistics

12 Feature Extraction Bracketed Features Ex:12th month of August 2013 can be realised as bracketed feature as Lexical Features in the phrase for this week the Lexical Features extracted are, and

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14 Drawbacks Pragmatic Ambiguity - this week parsed as next week or whether next weekend refers to the coming or subsequent weekend Semantic Errors – February the 30 th or Friday the 13 th this year Bad Reference Time - Assuming that the reference time of an utterance is the publication time of the article

15 References Language-Independent Discriminative Parsing of Temporal Expressions - Gabor Angeli, Jakob Uszkoreit Parsing Time: Learning to Interpret Time Expressions -Gabor Angeli, Chris Manning, Dan Jurafsky Hierarchical phrase-based translation. - David Chiang


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