This paper investigates whether surprisal theory can account for differential processing difficulty in the NP-/S-coordination ambiguity in Dutch. Surprisal is estimated using a Probabilistic Context-Free Grammar (PCFG), which is induced from an automatically annotated corpus. We find that our lexicalized surprisal model can account for the reading time data from a classic experiment on this amb...

This paper discusses logics whose premisses and/or conclusions can contain ambiguous material. Two diierent kinds of applications are sketched for these logics. First, the paper discusses how logics with ambiguous expressions can shed light on the way in which human hearers or readers understand certain`paradoxical' logical arguments, in which crucial use is made of ambiguous material. Second, ...

Words are considered semantically ambiguous if they have more than one meaning and can be used in multiple contexts. A number of recent studies have provided objective ambiguity measures by using a corpus-based approach and have demonstrated ambiguity advantages in both naming and lexical decision tasks. Although the predictive power of objective ambiguity measures has been examined in several ...

In order to considerably reduce the ambiguity rate, we propose in this article a disambiguation approach that is based on the selection of the right diacritics at different analysis levels. This hybrid approach combines a linguistic approach with a multi-criteria decision one and could be considered as an alternative choice to solve the morpho-lexical ambiguity problem regardless of the diacrit...

In this paper we compare two types of corpus, focusing on the lexical ambiguity of each of them. The first corpus consists mainly of general newspaper articles and literature excerpts, while the second belongs to the medical domain. To conduct the study, we have used two different disambiguation tools. First, each tool was validated in its respective application area. We then use these systems ...

We present a method for detecting and resolving lexical ambiguity in information retrieval queries. Leveraging existing word sense disambiguation tools, we define a measure of query term ambiguity based on the distribution of word senses in the relevant document set. If a query term is ambiguous, we allow the user to select the correct sense of the query term, in the style of Google’s spelling ...

This paper presents a statistical decision procedure for lexical ambiguity resolution. The algorithm exploits both local syntactic patterns and more distant collocational evidence, generating an efficient, effective, and highly perspicuous recipe for resolving a given ambiguity. By identifying and utilizing only the single best disambiguating evidence in a target context, the algorithm avoids t...

This paper presents a statistical decision procedure for lexical ambiguity resolution. The algorithm exploits both local syntactic patterns and more distant collo-cational evidence, generating an eecient, eeective, and highly perspicuous recipe for resolving a given ambiguity. By identifying and utilizing only the single best dis-ambiguating evidence in a target context, the algorithm avoids th...

Human language is massively ambiguous, yet we are generally able to identify the intended meanings of the sentences we hear and read quickly and accurately. How we manage and resolve ambiguity incrementally during real-time language comprehension given our cognitive resources and constraints is a major question in human cognition. Previous research investigating resource constraints on lexical ...

The Natural language question (NLQ) processing module is considered a fundamental component in the natural language interface of a Question Answering (QA) system, and its quality impacts the performance of the overall QA system. The most difficult problem in developing a QA system is so hard to find an exact answer to the NLQ. One of the most challenging problems in returning answers is how to ...