搜索结果: 1-7 共查到“应用语言学 Coreference Resolution”相关记录7条 . 查询时间(0.078 秒)
We describe a structure learning system for unrestricted coreference resolution that explores two key modeling techniques: latent coreference trees and automatic entropy-guided feature induction. The ...
A Constraint-Based Hypergraph Partitioning Approach to Coreference Resolution
Hypergraph Partitioning Approach Coreference Resolution
2015/9/11
This work is focused on research in machine learning for coreference resolution. Coreference resolution is a natural language processing task that consists of determining the expressions in a discours...
Deterministic Coreference Resolution Based on Entity-Centric,Precision-Ranked Rules
Coreference Resolution Entity-Centric Precision-Ranked Rules
2015/9/11
We propose a new deterministic approach to coreference resolution that combines the global information and precise features of modern machine-learning models with the transparency and modularity of de...
A Machine Learning Approach to Coreference Resolution of Noun Phrases
Noun Phrases Coreference Resolution
2015/8/26
In this paper, we present a learning approach to coreference resolution of noun phrases in unrestricted text. The approach learns from a small, annotated corpus and the task includes resolving
not ju...
Stanford’s Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task
Stanford Coreference Resolution System CoNLL-2011 Shared Task
2015/6/10
This paper details the coreference resolution system submitted by Stanford at the CoNLL- 2011 shared task. Our system is a collection of deterministic coreference resolution models that incorporate le...
Most coreference resolution models determine if two mentions are coreferent using a single function over a set of constraints or features.This approach can lead to incorrect decisions as lower precisi...
Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules
Coreference Resolution Entity-Centric Precision-Ranked Rules
2015/6/10
We propose a new deterministic approach to coreference resolution that combines the global information and precise features of modern machine-learning models with the transparency and modularity of de...