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[PDF] Top 20 Supersense Tagging of Unknown Nouns Using Semantic Similarity

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Supersense Tagging of Unknown Nouns Using Semantic Similarity

Supersense Tagging of Unknown Nouns Using Semantic Similarity

... After the raw text has been POS tagged and chunked, the grammatical relation extraction algorithm is run over the chunks. This consists of five passes over each sen- tence that first identify noun and verb phrase heads ... See full document

8

Supersense Tagging of Unknown Nouns in WordNet

Supersense Tagging of Unknown Nouns in WordNet

... We present a new framework for classify- ing common nouns that extends named- entity classification. We used a fixed set of 26 semantic labels, which we called su- persenses. These are the labels used by ... See full document

8

Automatic Semantic Classification for Chinese Unknown Compound Nouns

Automatic Semantic Classification for Chinese Unknown Compound Nouns

... for semantic classification is 84% and 81% for the first hundred samples and the second hundred samples ...not semantic com- position of the meanings of their morphological ...multiple semantic ... See full document

7

WikiSense: Supersense Tagging of Wikipedia Named Entities Based WordNet

WikiSense: Supersense Tagging of Wikipedia Named Entities Based WordNet

... Many avenues present themselves for future research and improvement of our system. For example, existing methods for pronoun resolution could be implemented to improve the quality of pronominal feature. Natural language ... See full document

10

Supersense Tagging for Arabic: the MT in the Middle Attack

Supersense Tagging for Arabic: the MT in the Middle Attack

... WordNet supersense tags denote coarse seman- tic classes, including person and artifact (for nouns) and motion and weather (for verbs); these categories can be taken as the top level of a ...Nominal ... See full document

7

Semantic Classification of Automatically Acquired Nouns using Lexico Syntactic Clues

Semantic Classification of Automatically Acquired Nouns using Lexico Syntactic Clues

... of unknown named entities (those never ap- pear in a training corpus) contain unknown mor- phemes as their constituents and that NER models perform poorly on ...acquire unknown morphemes and to ... See full document

9

Coarse Lexical Semantic Annotation with Supersenses: An Arabic Case Study

Coarse Lexical Semantic Annotation with Supersenses: An Arabic Case Study

... the supersense categories (originally, “lexicographer classes”) were intended to partition all English noun and verb senses into broad groupings, or semantic fields (Miller, 1990; Fellbaum, ...automatic ... See full document

6

Automatic Semantic Tagging of Unknown Proper Names

Automatic Semantic Tagging of Unknown Proper Names

... Proper noun recognition is initially performed in two steps: 1 common proper nouns are identified using a gazetteer, structured in files and related lists of trigger words for each prope[r] ... See full document

7

BaseNP Supersense Tagging for Japanese Texts

BaseNP Supersense Tagging for Japanese Texts

... different semantic category hierarchies for common nouns, proper nouns, and ...2,710 semantic classes, defined for over 264,312 nouns, with a maximum depth of twelve (Ikehara et ...for ... See full document

8

A Multi Domain Web Based Algorithm for POS Tagging of Unknown Words

A Multi Domain Web Based Algorithm for POS Tagging of Unknown Words

... To show that the run time overhead created by our algorithm is small, we measured its time per- formance (using an Intel Xeon 3.06GHz, 3GB RAM computer). The average time it took the best configuration of our ... See full document

9

Comprehensive Supersense Disambiguation of English Prepositions and Possessives

Comprehensive Supersense Disambiguation of English Prepositions and Possessives

... The new hierarchy and annotation guidelines were developed by consensus. The original preposi- tion supersense annotations were placed in a spread- sheet and discussed. While most tokens were un- ambiguously ... See full document

12

Automatic lexical semantic classification of nouns

Automatic lexical semantic classification of nouns

... lexical semantic classes gather together properties that appear to be linguistically significant for a number of linguistic ...lexical semantic classes as features that ordered the nominal meaning hierarchy ... See full document

8

Consistent Translation of Repeated Nouns using Syntactic and Semantic Cues

Consistent Translation of Repeated Nouns using Syntactic and Semantic Cues

... We tested the method with the three feature types and the four classifiers, i.e. 12 cases per lan- guage. On ZH/EN, a small increase of BLEU is observed in 5 cases (0.01), a decrease in two cases (0.02), and no variation ... See full document

10

Using Semantic Distance to Automatically Suggest Transfer Course Equivalencies

Using Semantic Distance to Automatically Suggest Transfer Course Equivalencies

... Table 1. Number of courses in the data sets Consider the small data set as an illustration. Each of the 25 MCC courses is compared with all 24 UML courses. All words are converted to low- ercase and punctuation is ... See full document

10

A Surya on Web Service Data Classification Discovery using Semantic Similarity

A Surya on Web Service Data Classification Discovery using Semantic Similarity

... This paper first classified OLAP schema design and data provisioning approaches that leverage SW technologies, based on the following criteria:Materialization, Transformations, Freshness, Structuredness, and ... See full document

5

Semantic Classification of Chinese Unknown Words

Semantic Classification of Chinese Unknown Words

... of unknown words makes a number of NLP (Natural Language Processing) tasks such as segmentation and word sense disambiguation more ...assigns semantic thesaurus categories to unknown Chinese ... See full document

8

An Ontology based Semantic Tagger for IE system

An Ontology based Semantic Tagger for IE system

... This task, like the named entity extraction task, an- notates words that are not instances of the ontol- ogy. Basically, for every chunk, we look for the first match with an instance concept. The match is based on the ... See full document

8

Causality and Similarity in Autobiographical Event Structure: An Investigation Using Event Cueing and Latent Semantic Analysis

Causality and Similarity in Autobiographical Event Structure: An Investigation Using Event Cueing and Latent Semantic Analysis

... structure using a modification of the traditional autobiographical event cueing procedure (Crovitz & Schiffman, 1974; Crovitz & Quina-Holland, 1976; Galton, 1883; Wagenaar, 1986; ... See full document

128

Opportunistic Semantic Tagging

Opportunistic Semantic Tagging

... As a matter of fact, often the texts of existing annotated corpora are not translated into other languages. Our assumption is that, even in this case, manually translating the annotated corpus and carrying out the ... See full document

6

Modeling Affirmative and Negated Action Processing in the Brain with Lexical and Compositional Semantic Models

Modeling Affirmative and Negated Action Processing in the Brain with Lexical and Compositional Semantic Models

... cooperating semantic alternatives to ...current semantic models are merely not a suit- able represenation for the negated ...modulates semantic similarity and lexico-semantic relations ... See full document

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