[PDF] Top 20 Semantic Parsing for Biomedical Event Extraction

... perform biomedical event extraction with the following ...HVS semantic parser. Finally, biomedical events are extracted from the HVS parse results using a hybrid method based on rules ... See full document

... learning semantic parsers with indirect super- vision, but existing work focuses almost ex- clusively on question ...tion extraction, yet such methods are often limited to binary relations and none can han- ... See full document

... an event anchor. If this was a single token, our event parser would be unable to link them since it cannot pre- dict self-loops in the dependency ...tic parsing, we use the self-trained ... See full document

... differences may pose problems in processing full- text articles. Since one of our goals was to determine the generality of our system across text types, we did not perform any full text-specific optimization. Our results ... See full document

... The table highlights some of our results. Firstly, we note that, in cases where we obtain a large number of extra sentences using distant supervi- sion (highlighted in the column “DS Sents”), we see a considerable gain ... See full document

... After basic tokenization and sentence segmentation, we generate a set of protein head tokens Prot (x) for each sentence x based on protein span defi- nitions from the shared task. To ensure tokens contain not more than ... See full document

... relation extraction, has been the sub- ject of much neural network based research in the past few ...no parsing or graph-like features, such as the multichannel convolutional neural network of Quan et ... See full document

... While tailored towards (biomedical) event extrac- tion, we believe that our models can also be ef- fective in a more general Semantic Role Label- ing (SRL) context. Using variants of Model 1, we can ... See full document

... application of different preprocessing steps. Miwa et al. (2010) presented a task-oriented comparison of five parsers, measuring their contribution to bio-molecular event extraction. They used domain models ... See full document

... the event extraction system also differ in the extent of the marked spans, with GENIA GGP marking the minimal name and GENETAG allow- ing also the inclusion of head nouns when a name occurs in modifier ... See full document

... 2011), event an- notations are converted into pseudo-syntactic rep- resentations and the task is solved as a syntactic extraction problem by traditional parsing meth- ...the event annotations ... See full document

... trigger/entity, event role, event structure, and hedge de- ...The event role detector determines which triggers/entities constitute arguments of events, links them to the appropriate event ... See full document

... Frame parsing is a Natural Language Understand- ing task that involves detecting in a sentence an event or a scenario, called Frame, as well as all the elements or roles that can be associated to this ... See full document

... of biomedical event ...and semantic features, such as N-gram features, walk subsequence features, predicate argument structure (PAS) features, especially some new features derived from a strategy ... See full document

... Nested event structures are a common occur- rence in both open domain and domain spe- cific extraction tasks, ...“crime” event can cause a “investigation” event, which can lead to an “arrest” ... See full document

... on biomedical event extrac- tion rely on kernel classification methods like the support vector machines (SVMs) (Bj¨orne and Salakoski, 2011; Venugopal et ...distributed semantic features. However, ... See full document

... the extraction of events involving proteins whose names are annotated in ...Each event has two types of arguments, Theme and Cause, which correspond respectively to the Agent and Patient roles in ... See full document

... overall event extraction performance has increased about three percentage points, the highest performance on the current GE- task being ...that event extraction is a hard problem, and that the ... See full document

... the event extraction task, using only the information available in the training corpus and modelling the task applying an approach similar to the one that has been applied to tasks like semantic role ... See full document

... Let us summarise the data and tools we employ. The data for our experiments is the GENIA Event Corpus (GEC) [1]. For feature generation, we employ the following tools. POS and NE tagging are performed with the ... See full document