This paper summarizes the annotation of fine-grained entailment relationships in the context of student answers to science assessment questions. We annotated a corpus of 15,357 answer pairs with 145,911 fine-grained entailment relationships. We provide the rationale for such fine-grained analysis and discuss its perceived benefits to an Intelligent Tutoring System. The corpus also has potential...

State of the art semi-supervised entity set expansion algorithms produce noisy results, which need to be refined manually. Sets expanded for intended fine-grained concepts are especially noisy because these concepts are not well represented by the limited number of seeds. Such sets are usually incorrectly expanded to contain elements of a more general concept. We show that fine-grained control ...

The island of Syros consists largely of possibly-repeated sequences of glaucophane-bearing calcareous schists, mafic schists, dolomite marbles, and calcite marbles containing abundant aragonite pseudomorphs (Dixon, 1969; Hecht, 1984). Several discrete, fault-bounded packages of blueschist/eclogite-facies mafic rocks with minor serpentinite are also found on the island. Although the mafic rocks ...

Light microscopic examination of the kidneys in 170 patients with multiple myeloma revealed three from patients without diabetes with glomerular nodules that were indistinguishable from those of diabetic glomerular sclerosis. Electron microscopic studies showed the nodules to be deposits of fine-grained material that corresponded to precipitations of protein but lacked the basement-membrane-lik...

In many QA systems, fine-grained named entities are extracted by coarse-grained named entity recognizer and fine-grained named entity dictionary. In this paper, we describe a fine-grained Named Entity Recognition using Conditional Random Fields (CRFs) for question answering. We used CRFs to detect boundary of named entities and Maximum Entropy (ME) to classify named entity classes. Using the pr...

Global sparse analysis framework aims to design precise, sound, yet scalable static analyzers systematically. The framework breaks the tradeoff between general-purpose but coarse-grained sparse analyses and fine-grained but limited-purpose sparse analyses by providing a general-purpose fine-grained sparse analysis framework. However, the formal aspect of the framework has not been presented rig...

Current lexical semantic theories provide representations at a coarse grained level. In this paper, I will provide motivations for a fine grained representation for verbs and. nouns. An initial case study is done to serve as evidence that a more detailed representation is needed for tasks that require high accuracy rates, such as machine translation. An automatic approach to gather fine grained...

Beneath slow-spreading ridges, melt bodies are generally considered to represent ephemeral magma reservoirs filled with crystal mushes. Formation of the oceanic crust requires at least partial extraction melts from these However, collection and processes yet be fully constrained. We investigate olivine gabbros plutonic section recovered IODP Hole U1473A, in Atlantis Bank Oceanic Core Complex (S...

We investigate the relation between fine-grained and coarse-grained distributed computations of a class of problems related to the generic transitive closure problem (TC for short). We choose an intricate systolic algorithm for the TC problem, by Guibas, Kung and Thompson (GKT algorithm for short), as a starting point due to its particularly close relationship to matrix multiplication. The GKT ...

Named Entity Recognition and Classification (NERC) is a well-studied NLP task typically focused on coarse-grained named entity (NE) classes. NERC for more fine-grained semantic NE classes has not been systematically studied. This paper quantifies the difficulty of fine-grained NERC (FG-NERC) when performed at large scale on the people domain. We apply unsupervised acquisition methods to constru...