Topic
Semantic property
About: Semantic property is a research topic. Over the lifetime, 1727 publications have been published within this topic receiving 52841 citations.
Papers published on a yearly basis
1 / 2
Papers
TL;DR: A range of semantic and pragmatic applications of the theory are examined, and a unitary principle specifying how the focus semantic value interacts with semantics and pragmatic processes is extracted.
Abstract: According to the alternative semantics for focus, the semantic reflec of intonational focus is a second semantic value, which in the case of a sentence is a set of propositions. We examine a range of semantic and pragmatic applications of the theory, and extract a unitary principle specifying how the focus semantic value interacts with semantic and pragmatic processes. A strong version of the theory has the effect of making lexical or construction-specific stipulation of a focus-related effect in association-with-focus constructions impossible. Furthermore, while focus has a uniform import, the sources of meaning differences in association with focus are various.
2,959 citations
TL;DR: Findings using an electrophysiological brain component, the N400, that reveal the nature and timing of semantic memory use during language comprehension support a view of memory in which world knowledge is distributed across multiple, plastic-yet-structured, largely modality-specific processing areas, and in which meaning is an emergent, temporally extended process.
2,189 citations
TL;DR: A system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame, based on statistical classifiers trained on roughly 50,000 sentences that were hand-annotated with semantic roles by the FrameNet semantic labeling project.
Abstract: We present a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame. Given an input sentence and a target word and frame, the system labels constituents with either abstract semantic roles, such as AGENT or PATIENT, or more domain-specific semantic roles, such as SPEAKER, MESSAGE, and TOPIC.The system is based on statistical classifiers trained on roughly 50,000 sentences that were hand-annotated with semantic roles by the FrameNet semantic labeling project. We then parsed each training sentence into a syntactic tree and extracted various lexical and syntactic features, including the phrase type of each constituent, its grammatical function, and its position in the sentence. These features were combined with knowledge of the predicate verb, noun, or adjective, as well as information such as the prior probabilities of various combinations of semantic roles. We used various lexical clustering algorithms to generalize across possible fillers of roles. Test sentences were parsed, were annotated with these features, and were then passed through the classifiers.Our system achieves 82% accuracy in identifying the semantic role of presegmented constituents. At the more difficult task of simultaneously segmenting constituents and identifying their semantic role, the system achieved 65% precision and 61% recall.Our study also allowed us to compare the usefulness of different features and feature combination methods in the semantic role labeling task. We also explore the integration of role labeling with statistical syntactic parsing and attempt to generalize to predicates unseen in the training data.
1,838 citations
TL;DR: Two versions of a “cohort”-based model of the process of spoken word-recognition are described, showing how it evolves from a partially interactive model, where access is strictly autonomous but selection is subject to top-down control, to a fully bottom-up model where context plays no role in the processes of form-based access and selection.
1,825 citations
[...]
TL;DR: To study the operational behaviour of λ-terms, this work will use the denotational (mathematical) approach to choose a space of semantics values, or denotations, where terms are to be interpreted.
Abstract: To study the operational behaviour of λ-terms, we will use the denotational (mathematical) approach. A denotational semantics for a language is based on the choice of a space of semantics values, or denotations, where terms are to be interpreted. Choosing a space with nice mathematical properties can help in proving the semantic properties of terms, since to this aim standard mathematical techniques can be used.
1,661 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2025 | 3 |
| 2024 | 5 |
| 2023 | 14 |
| 2022 | 16 |
| 2021 | 51 |
| 2020 | 54 |