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によって ANDREA CAROLINA SILVA COQUE 7か月前.

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SEMANTIC FEATURES AND SELECTION RESTRICTIONS

The text discusses the role and application of semantic features within natural language processing (NLP). It outlines the importance of semantic features in various NLP problems, such as revealing predicate-argument relationships and combining verbs with adverbs indicating time, place, and purpose.

SEMANTIC FEATURES AND SELECTION RESTRICTIONS

GROUP 8 --Rubio Anthony --Rueda Alexander --Sanchez Allison --Silva Andrea --Solis Melany

SEMANTIC FEATURES AND SELECTION RESTRICTIONS

2. SEMANTIC FEATURE ACCORDING TO U. WEINREICH

The semantic feature has several purposes:
Add provisional semantic content to an ambiguous word
Explain deviant and metaphorical readings
As a basis for semantic agreement
The distinction made it possible to use
The notion in a broader sense

than in transformational grammar

U. Weinreich proposed
A distinction between a paradigmatic semantic feature and a transfer function.

5. ON SEMANTIC INVARIANT OF THE CLASS OF WORDS WITH GENITIVE SUBJECT

Example
Demonstrating how the presence or absence of the presupposition of existence affects the choice of case for the subject.
Clarification that if the verb's meaning doesn't definitively predict the presence of the presupposition of existence
Identification of two semantic components
'X takes place'
'X exists'

Determines the case of the subject in negative sentences.

Focus on
Specifically in contrast with the nominative case.
The construction with genitive subject in Russian,

4. SEMANTIC FEATURES AND SELECTION RESTRICTIONS IN LEXICON AND GRAMMAR

Role in regulating selection restrictions
Examples

Semantic motivations for syntactic behaviors

Predicates introducing indirect question

Semantic distribution of conjunctions

Neg-Raising predicates

Evolution of semantic theory

3. SEMANTIC FEATURES IN SYSTEMS OF NATURAL LANGUAGE PROCESSING (NLP)

You can list NLP problems in which features are constantly used
Transfer semantic features can be used to distinguish texts that allow liberal interpretations of deviant or metaphorical texts.
Semantic features can be useful in the process
Combination of verbs with adverbs that designate time place reason purpose instrument, etc.
Disambiguation of a lexically homonymous predicated word
Revealing predicate-argument relationships in parsing algorithms
Semantic features belong to NLP resources

1. LEXICAL DATABASE OF THE SYSTEM

It consists of 2 basic components:
Bibliographic Database (BBD)

Contains bibliographic information on individual lexemes

Syntactic and Semantic information cannot be found in existing dictionaries

The vocabulary consists of about 12,500 words

Lexical Database (LBD)

Consists of several domains

The user can obtain information about:

--Morphology --Syntactic features --Semantic features --Prosody --Referential features of individual lexical items.

Vocabulary presented in machine-readable format

Expert System for natural language processing purposes