Simple Negation Scope Resolution through Deep Parsing: A Semantic Solution to a Semantic Problem

نویسندگان

  • Woodley Packard
  • Emily M. Bender
  • Jonathon Read
  • Stephan Oepen
  • Rebecca Dridan
چکیده

In this work, we revisit Shared Task 1 from the 2012 *SEM Conference: the automated analysis of negation. Unlike the vast majority of participating systems in 2012, our approach works over explicit and formal representations of propositional semantics, i.e. derives the notion of negation scope assumed in this task from the structure of logical-form meaning representations. We relate the task-specific interpretation of (negation) scope to the concept of (quantifier and operator) scope in mainstream underspecified semantics. With reference to an explicit encoding of semantic predicate-argument structure, we can operationalize the annotation decisions made for the 2012 *SEM task, and demonstrate how a comparatively simple system for negation scope resolution can be built from an off-the-shelf deep parsing system. In a system combination setting, our approach improves over the best published results on this task to date.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Learning the Scope of Negation via Shallow Semantic Parsing

s Papers Clinical PCLB PCRB PCS PCLB PCRB PCS PCLB PCRB PCS autoparse(t&t) 91.97 87.82 80.88 85.45 67.20 59.26 97.48 88.30 85.89 autoparse(test) 92.71 88.33 81.84 87.57 68.78 62.70 97.48 87.73 85.21 oracle 99.72 94.59 94.37 98.94 84.13 83.33 99.89 98.39 98.39 Table 5: Performance (%) of negation scope finding on the three subcorpora by using automatic parser trained with 6,691 sentences in GTB1...

متن کامل

برچسب‌زنی خودکار نقش‌های معنایی در جملات فارسی به کمک درخت‌های وابستگی

Automatic identification of words with semantic roles (such as Agent, Patient, Source, etc.) in sentences and attaching correct semantic roles to them, may lead to improvement in many natural language processing tasks including information extraction, question answering, text summarization and machine translation. Semantic role labeling systems usually take advantage of syntactic parsing and th...

متن کامل

Addressing Semantic Ambiguities in Natural Language Constraints

In NL2OCL project, we aim to translate English specification of constraints to formal constraints such as OCL (Object Constraint Language). In English to OCL translation, our contribution is a semantic analyzer that uses the output of the Stanford parser for shallow and deep semantic parsing. Our analysis of the output of shallow semantic parsing showed that semantic roles were misidentified fo...

متن کامل

A Context-aware Architecture for Mental Model Sharing through Semantic Movement in Intelligent Agents

Recent studies in multi-agent systems are paying increasingly more attention to the paradigm of designing intelligent agents with human inspired concepts. One of the main cognitive concepts driving the core of many recent approaches in multi agent systems is shared mental models. In this paper, we propose an architecture for sharing mental models based on a new concept called semantic movement....

متن کامل

برچسب‌زنی نقش معنایی جملات فارسی با رویکرد یادگیری مبتنی بر حافظه

Abstract Extracting semantic roles is one of the major steps in representing text meaning. It refers to finding the semantic relations between a predicate and syntactic constituents in a sentence. In this paper we present a semantic role labeling system for Persian, using memory-based learning model and standard features. Our proposed system implements a two-phase architecture to first identify...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014