OPERA: Operations-oriented Probabilistic Extraction, Reasoning, and Analysis

Abstract

The OPERA system (for Operations-oriented Probabilistic Extraction, Reasoning, and Analysis) developed jointly by CMU and USC/ISI is an integrated solution to the challenges of DARPAs Active Interpretation of Disparate Alternatives (AIDA) program in the form of: (i) high-performance media analysis (TA1) for text, speech, and image/video data, (ii) semantic representation and reasoning support (TA1 and TA2), (iii) cross-medium and cross-language integration (TA2), and (iv) hypothesis creation, management, and hypothesis exploration (TA3). Given that all required components of such a system are still active areas of research, the creation of a single system (pipelined or otherwise) has the potential for a substantial rate of compounded errors. Early versions of the system created had strong abstraction boundaries for limited information sharing between systems. Later incarnations benefited from allowing for the output of extractors to be coupled with raw text strings and embedding vectors. These prove especially advantageous in the presence of large-scale language models that encode world knowledge, and when aligning predictions to an open-domain ontology, like that of WikiData.

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Document Details

Document Type
Technical Report
Publication Date
Jan 19, 2023
Accession Number
AD1190961

Entities

People

  • Hans Chalupsky
  • Yonatan Bisk

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automated Speech Recognition
  • Computational Linguistics
  • Computational Science
  • Computer Languages
  • Computer Vision
  • Detection
  • Engineering
  • Information Exchange
  • Language
  • Medical Personnel
  • Natural Language Processing
  • Natural Languages
  • Ontologies
  • Personnel Management
  • Reasoning

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Linguistics
  • Distributed Systems and Data Platform Development