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Semantic Role Labeling

39 papers with code · Natural Language Processing

Semantic role labeling aims to model the predicate-argument structure of a sentence and is often described as answering "Who did what to whom". BIO notation is typically used for semantic role labeling.

Example:

Housing starts are expected to quicken a bit from August’s pace
B-ARG1 I-ARG1 O O O V B-ARG2 I-ARG2 B-ARG3 I-ARG3 I-ARG3

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Greatest papers with code

Deep contextualized word representations

NAACL 2018 zalandoresearch/flair

We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e. g., syntax and semantics), and (2) how these uses vary across linguistic contexts (i. e., to model polysemy).

CITATION INTENT CLASSIFICATION COREFERENCE RESOLUTION LANGUAGE MODELLING NAMED ENTITY RECOGNITION NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SEMANTIC ROLE LABELING SENTIMENT ANALYSIS

AllenNLP: A Deep Semantic Natural Language Processing Platform

WS 2018 allenai/allennlp

This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding.

READING COMPREHENSION SEMANTIC ROLE LABELING

Deep Semantic Role Labeling: What Works and What's Next

ACL 2017 luheng/deep_srl

We introduce a new deep learning model for semantic role labeling (SRL) that significantly improves the state of the art, along with detailed analyses to reveal its strengths and limitations.

PREDICATE DETECTION

Deep Semantic Role Labeling with Self-Attention

5 Dec 2017XMUNLP/Tagger

Semantic Role Labeling (SRL) is believed to be a crucial step towards natural language understanding and has been widely studied.

SEMANTIC ROLE LABELING

Linguistically-Informed Self-Attention for Semantic Role Labeling

EMNLP 2018 strubell/LISA

Unlike previous models which require significant pre-processing to prepare linguistic features, LISA can incorporate syntax using merely raw tokens as input, encoding the sequence only once to simultaneously perform parsing, predicate detection and role labeling for all predicates.

DEPENDENCY PARSING MULTI-TASK LEARNING PART-OF-SPEECH TAGGING PREDICATE DETECTION SEMANTIC ROLE LABELING (PREDICTED PREDICATES) WORD EMBEDDINGS

Glyce: Glyph-vectors for Chinese Character Representations

29 Jan 2019ShannonAI/glyce

However, due to the lack of rich pictographic evidence in glyphs and the weak generalization ability of standard computer vision models on character data, an effective way to utilize the glyph information remains to be found.

CHINESE WORD SEGMENTATION DEPENDENCY PARSING DOCUMENT CLASSIFICATION IMAGE CLASSIFICATION LANGUAGE MODELLING MACHINE TRANSLATION MULTI-TASK LEARNING PART-OF-SPEECH TAGGING SEMANTIC ROLE LABELING SEMANTIC TEXTUAL SIMILARITY SENTENCE CLASSIFICATION SENTIMENT ANALYSIS