Teleonomy

The distinction between teleology and teleonomy that biologists sometimes refer to seems to be helpful in certain contexts, but it is used in several different ways and has rarely been clearly drawn. This paper discusses three prominent uses of the term “teleonomy” and traces its history back to what seems to be its first use. This use is examined in detail and then justified and refined on the basis of elements found in the philosophy of Aristotle, Kant, Anscombe and others. In the course of this explication, it will also be shown how the description of end-directed processes relates to their explanation

Applying Reliability Metrics to Co-Reference Annotation

Studies of the contextual and linguistic factors that constrain discourse phenomena such as reference are coming to depend increasingly on annotated language corpora. In preparing the corpora, it is important to evaluate the reliability of the annotation, but methods for doing so have not been readily available. In this report, I present a method for computing reliability of coreference annotation. First I review a method for applying the information retrieval metrics of recall and precision to coreference annotation proposed by Marc Vilain and his collaborators. I show how this method makes it possible to construct contingency tables for computing Cohen's Kappa, a familiar reliability metric. By comparing recall and precision to reliability on the same data sets, I also show that recall and precision can be misleadingly high. Because Kappa factors out chance agreement among coders, it is a preferable measure for developing annotated corpora where no pre-existing target annotation exists.Comment: 10 pages, 2-column format; uuencoded, gzipped, tarfil

LangPro: Natural Language Theorem Prover

LangPro is an automated theorem prover for natural language (https://github.com/kovvalsky/LangPro). Given a set of premises and a hypothesis, it is able to prove semantic relations between them. The prover is based on a version of analytic tableau method specially designed for natural logic. The proof procedure operates on logical forms that preserve linguistic expressions to a large extent. %This property makes the logical forms easily obtainable from syntactic trees. %, in particular, Combinatory Categorial Grammar derivation trees. The nature of proofs is deductive and transparent. On the FraCaS and SICK textual entailment datasets, the prover achieves high results comparable to state-of-the-art.Comment: 6 pages, 8 figures, Conference on Empirical Methods in Natural Language Processing (EMNLP) 201