This paper presents a Natural Language Processing (NLP) approach to filter Named Entities (NE) from a list of collocation candidates. The NE are defined as the names of ’People’, ’Places’, ’Organizations’, ’Software’, ’Illnesses’, and so forth. The proposed method is based on statistical measures associated with Web resources to identify NE. Our method has three stages: (1) Building artificial ...

This paper reports on experiments in classifying the semantic role annotations assigned to prepositional phrases in both PENN TREEBANK (version II) and FRAMENET (version 0.75). In both cases, experiments are done to see how the prepositions can be classified given the dataset’s role inventory, using standard word-sense disambiguation features, such as the parts of speech of surrounding words, a...

Natural languages are full of collocations, recurrent combinations of words that co-occur more often than expected by chance and that correspond to arbitrary word usages. Recent work in lexicography indicates that collocations are pervasive in English; apparently, they are common in all types of writing, including both technical and nontechnical genres. Several approaches have been proposed to ...

Statistical-based collocation extraction approaches suffer from (1) low precision rate because high co-occurrence bi-grams may be syntactically unrelated and are thus not true collocations; (2) low recall rate because some true collocations with low occurrences cannot be identified successfully by statistical-based models. To integrate both syntactic rules as well as semantic knowledge into a s...

The present work is a pilot study of English lexical collocations in written productions by advanced Italian students of English. The aim is to describe errors made by learners in the production of word combinations. First a working definition of lexical collocation will be given in order to identify those word combinations that will be taken into consideration. Then, after introducing the data...

Collocation has been considered a problematic area for L2 learners. Various studies have been conducted to investigate native speakers‘ (NS) and non-native speakers‘ (NNS) use of different types of collocations (e.g., Durrant and Schmitt, 2009; Laufer and Waldman, 2011).These studies have indicated that, unlike NS, NNS rely on a limited set of collocations and tend to overuse them. This raises ...

In this paper, we explore complex network properties of word collocation networks (Ferret, 2002) from four different genres. Each document of a particular genre was converted into a network of words with word collocations as edges. We analyzed graphically and statistically how the global properties of these networks varied across different genres, and among different network types within the sa...

Abstract We describe tools for the extraction of collocations not only in the form of word combinations, but also of data about the morphosyntactic properties of collocation candidates. Such data are needed for a detailed lexical description of collocations, and to support both their recognition in text and the generation of collocationally acceptable text. We describe the tool architecture, re...

To date, substantial efforts have been devoted to the extraction of collocations from text corpora. However, only a few works deal with the subsequent processing of results in order for these to be successfully integrated into the NLP applications that could benefit from them (e.g., machine translation). This paper presents an accurate method for identifying translation equivalents of collocati...

to investigate the effect of massed and distributed collaborative and non-collaborative presentation on l2 learners’ comprehension and production of lexical collocations, 105 participants at takestan islamic azad university in 4 groups were assigned to four different treatment conditions (collaborative-massed; collaborative-distributed; noncollaborative-massed; and noncollaborative-distributed ...