Word Embeddings for Entity-annotated Texts

Learned vector representations of words are useful tools for many information retrieval and natural language processing tasks due to their ability to capture lexical semantics. However, while many such tasks involve or even rely on named entities as central components, popular word embedding models have so far failed to include entities as first-class citizens. While it seems intuitive that annotating named entities in the training corpus should result in more intelligent word features for downstream tasks, performance issues arise when popular embedding approaches are naively applied to entity annotated corpora. Not only are the resulting entity embeddings less useful than expected, but one also finds that the performance of the non-entity word embeddings degrades in comparison to those trained on the raw, unannotated corpus. In this paper, we investigate approaches to jointly train word and entity embeddings on a large corpus with automatically annotated and linked entities. We discuss two distinct approaches to the generation of such embeddings, namely the training of state-of-the-art embeddings on raw-text and annotated versions of the corpus, as well as node embeddings of a co-occurrence graph representation of the annotated corpus. We compare the performance of annotated embeddings and classical word embeddings on a variety of word similarity, analogy, and clustering evaluation tasks, and investigate their performance in entity-specific tasks. Our findings show that it takes more than training popular word embedding models on an annotated corpus to create entity embeddings with acceptable performance on common test cases. Based on these results, we discuss how and when node embeddings of the co-occurrence graph representation of the text can restore the performance.Comment: This paper is accepted in 41st European Conference on Information Retrieva

Light Quark Physics with Dynamical Wilson Fermions

We present results for spectroscopy, quark masses and decay constants obtained from SESAM's and TkL's large statistics simulations of QCD with two dynamical Wilson fermions.Comment: 3 pages; to appear in the proceedings of Lat.'9

Glueballs and string breaking from full QCD

We present results on the static potential, and torelon and glueball masses from simulations of QCD with two flavours of dynamical Wilson fermions on $16^3\times 32$ and $24^3\times 40$ lattices at $\beta=5.6$.Comment: Talk presented by Gunnar Bali at International Symposium on Lattice Field Theories (Lattice 97), Edinburgh, July 1997, 3 pages LaTeX (epscrc2.sty) with 4 eps figure

Critical Dynamics of the Hybrid Monte Carlo Algorithm

We investigate the critical dynamics of the Hybrid Monte Carlo algorithm approaching the chiral limit of standard Wilson fermions. Our observations are based on time series of lengths O(5000) for a variety of observables. The lattice sizes are 16^3 x 32 and 24^3 x 40. We work at beta=5.6, and kappa=0.156, 0.157, 0.1575, 0.158, with 0.83 > m_pi/m_rho > 0.55. We find surprisingly small integrated autocorrelation times for local and extended observables. The dynamical critical exponent $z$ of the exponential autocorrelation time is compatible with 2. We estimate the total computational effort to scale between V^2 and V^2.25 towards the chiral limit.Comment: 3 pages, Latex with espcrc2.sty and postscript figures, Talk given at Lattice 9

Congenital tumors and nonimmune hydrops fetalis

Peer Reviewe

ArgoNeuT and the Neutrino-Argon Charged Current Quasi-Elastic Cross Section

ArgoNeuT, a Liquid Argon Time Projection Chamber in the NuMI beamline at Fermilab, has recently collected thousands of neutrino and anti-neutrino events between 0.1 and 10 GeV. The experiment will, among other things, measure the cross section of the neutrino and anti-neutrino Charged Current Quasi-Elastic interaction and analyze the vertex activity associated with such events. These topics are discussed along with ArgoNeuT's automated reconstruction software, currently capable of fully reconstructing the muon and finding the event vertex in neutrino interactions.Comment: 6 pages, 4 figures, presented at the International Nuclear Physics Conference, Vancouver, Canada, July 4-9, 2010, to be published in Journal of Physics: Conference Series (JPCS