Detecting Compositionality in Multi-Word Expressions

TY - CONF

T1 - Detecting Compositionality in Multi-Word Expressions

AU - Korkontzelos, Ioannis

AU - Manandhar, Suresh

PY - 2009

Y1 - 2009

N2 - Identifying whether a multi-word expression (MWE) is compositional or not is important for numerous NLP applications. Sense induction can partition the context of MWEs into semantic uses and therefore aid in deciding compositionality. We propose an unsupervised system to explore this hypothesis on compound nominals, proper names and adjective-noun constructions, and evaluate the contribution of sense induction. The evaluation set is derived from WordNet in a semisupervised way. Graph connectivity measures are employed for unsupervised parameter tuning.

AB - Identifying whether a multi-word expression (MWE) is compositional or not is important for numerous NLP applications. Sense induction can partition the context of MWEs into semantic uses and therefore aid in deciding compositionality. We propose an unsupervised system to explore this hypothesis on compound nominals, proper names and adjective-noun constructions, and evaluate the contribution of sense induction. The evaluation set is derived from WordNet in a semisupervised way. Graph connectivity measures are employed for unsupervised parameter tuning.

UR - http://www.scopus.com/inward/record.url?scp=84857154268&partnerID=8YFLogxK

M3 - Paper

SP - 65

EP - 68

ER -