sometimes there comes a pronoun after a common [individual], which has apparently been used as the object of a legal decision (ḥukm), and by means of external evidence, the certainty is achieved that this pronoun refers to some common individuals. then, the question arises as to whether reference of the pronoun to some common individuals would cause its designation or the common generality cont...

A recent paper (Beaver, 2004) recasts the Centering algorithm for pronoun resolution (Brennan et al., 1987) in terms of optimality theory (OT). Although the limitations of centering for pronoun resolution are well known, the algorithm's restatement in OT highlights the strengths of centering and produces an algorithm whose behavior is more transparent to the developer. The authors' motivation f...

We describe the design, the evaluation setup, and the results of the DiscoMT 2015 shared task, which included two subtasks, relevant to both the machine translation (MT) and the discourse communities: (i) pronoun-focused translation, a practical MT task, and (ii) cross-lingual pronoun prediction, a classification task that requires no specific MT expertise and is interesting as a machine learni...

In Korean, in order to generate a coherent text, a redundantly prominent noun should be replaced by a non-zero pronoun or zero pronoun. Otherwise, the text becomes unnatural. Specifically, a redundant noun in Korean is frequently omitted while a redundant noun in English is replaced by a pronoun. This paper proposes a generation algorithm of the zero pronoun, using a Cost-based Centering Model ...

The first part of this commentary discusses the minimal requirements that any serious theory of language acquisition must meet. It must take into account the particular properties of the human language processor and the (linguistic and nonlinguistic) input, as well as the specific motivation which causes the learner to apply the former to the latter. Neglecting, or even not keeping constant, so...

An embodied language-learning system is presented that can learn the correct deictic meanings for the words “I” and “you.” The system uses contextual clues from already understood words and sensory information from its environment to determine the most likely grounding for a new word. The system also serves as a model for the phenomenon of pronoun reversal among congenitally blind children, as ...

This paper investigates the problem of Chinese zero pronoun resolution. Most existing approaches are based on machine learning algorithms, using hand-crafted features, which is labor-intensive. Moreover, semantic information that is essential in the resolution of noun phrases has not been addressed enough by previous approaches on zero pronoun resolution. This is because that zero pronouns have...

We present a cognitive computational model of pronoun resolution that reproduces the human interpretation preferences of the Subject Assignment Strategy and the Parallel Function Strategy. Our model relies on a probabilistic pronoun resolution system trained on corpus data. Factors influencing pronoun resolution are represented as features weighted by their relative importance. The importance t...

We present an automatic approach to determining whether a pronoun in text refers to a preceding noun phrase or is instead nonreferential. We extract the surrounding textual context of the pronoun and gather, from a large corpus, the distribution of words that occur within that context. We learn to reliably classify these distributions as representing either referential or non-referential pronou...