[PDF] Top 20 Joint Unsupervised Coreference Resolution with Markov Logic

... Markov logic makes it possible to compactly specify probability distributions over complex re- lational ...sampling” Markov chain Monte Carlo ...the Markov chain mixes very ... See full document

... Several unsupervised learning algorithms have been applied to coreference ...perform joint inference across mentions by using Markov ... See full document

... E1 corefers to E2, and E3 does to E4. E2 is more abstract than E1, and has less evidence of being an event. E4 is a pronoun, and thus may seem to refer to an entity rather than an event. Thus, E2 and E4 are relatively ... See full document

... performs joint event coreference res- olution and anaphoricity ...event coreference resolution was inspired by the difficulty of designing a standalone system for deter- mining the ... See full document

... and coreference resolution jointly (§4). Our joint model is inspired by re- cent work in coreference resolution that indepen- dently ranks the possible mention’s antecedents, forming a ... See full document

... To infer the true posterior probability of P ( Z | X ), we follow (Teh et al., 2006) and use the Gibbs sampling algorithm (Geman and Ge- man, 1984) based on the direct assignment sam- pling scheme. In this sampling ... See full document

... Event coreference resolution is a challenging problem since it relies on several components of the information extraction pipeline that typically yield noisy ...event coreference resolver, and ... See full document

... entity coreference resolution has received much attention from the compu- tational linguistic researchers, there is only limited work that incorporates event-related information to solve entity ... See full document

... Pairwise coreference resolution models must merge pairwise coreference decisions to gen- erate final ...a joint learning model which combines pairwise classification and mention clustering ... See full document

... described in Chang et al. (2013) in our experiments. The task of mention detection is closely related to Named Entity Recognition (NER). Punyakanok and Roth (2001) thoroughly study phrase identifica- tion in sentences ... See full document

... M¨uller et al. (2002) used co-training for coref- erence resolution, a semi-supervised method. Co- training puts features into disjoint subsets when learning from labeled and unlabeled data and tries to leverage ... See full document

... Another global approach to coreference is the application of Conditional Random Fields (CRFs) (McCallum and Wellner, 2004). Although both are global approaches, CRFs and ILP have important differences. ILP uses ... See full document

... pairwise coreference relations and generative modeling of cluster distri- butions, and thus allows for both probabilistic in- ference over event clusters and easy incorporation of pairwise linking ... See full document

... This paper presented an expressive entity-mention model for coreference resolution by using Inductive Logic Programming. In contrast to the traditional mention-pair model, our model can capture ... See full document

... The first block in Table 4 indicates that lemma matching is a strong baseline for event resolution. Most of the event scores for Baseline 1 are actually higher than the corresponding entity scores, which were ... See full document

... CV (Cybulska and Vossen, 2015a) is a super- vised method for event coreference, based on dis- crete features. They first cluster documents to top- ics, and then cluster coreferring mentions within each topic ... See full document

... improve coreference resolution, but did not con- sider a joint ...and joint modeling in particular, since it outperforms the state-of-the-art Stanford sieve system (winner of the CoNLL 2011 ... See full document

... an unsupervised approach that partitions noun phrases into coreferent groups through clustering ...anaphora resolution using unsupervised methods to extract useful information, such as gender and ... See full document

... (Poesio and Kabadjov, 2004) and BART (Versley et al., 2008) (which can be considered a succes- sor of GuiTaR) are both modular systems that tar- get the full coreference resolution task. As such, both ... See full document

... for coreference resolution: one link component computes how likely a mention is coreferential with a candidate entity; the other compo- nent, called creation model, computes the probability that a mention ... See full document