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Making Sense of Human - Human Conversation
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Data and SW





Corpora

Software

  • Syntactic parser (Macaon): This module provides sentence-level part-of-speech tagging and syntactic parses.
  • Semantic parser (Fastsem): This module performs sentence-level FrameNet semantic analysis of speech and social media text, given syntactic analyses provided by the syntactic parser.
  • Synopsis generator: This module generates synopses of speech conversations by recombining training data synopses and filling detected concept slot.
  • Sentiment analyser (SemEval2016): This module can predict the sentiment polarity of short text messages.
  • Abstractive cluster labeller: This rest service will label a textual piece with a label (abstractive) using DBpedia
  • Computation platform: This module helps with the integration of the various components as a general pipeline. It provides REST services and repository integration for other components.
  • Coreference resolver (BART): This module resolves coreferences in conversations.
  • Website parsers: These parsers can be used to crawl a range of websites for online conversations.
  • Discourse Parser (CoNLL2016): This system provides PDTB-style discourse parsing for written English text.
  • Agreement predictor (ADRian): This system provides agree/disagree classification in social media (used in social media prototype template-based summarisation, sense-eu).
  • Mood predictor (coMOOD): This system provides mood prediction (used in social media prototype template-based summarisation, sense-eu)
  • Repository: The conversation repository can store conversations and analyses generated by other modules. It is the central synchronization point of the pipeline.
  • Repository tools: Tools for easily accessing the repository from the command line
  • Comment clustering and summarization: This system can link comments in a conversation, cluster them and generate a summary from the clusters.
  • Event/sentiment detector (GATE): This system provides standard NLP, named-entity recognition, event detection, sentiment detection.
    • Models: English
    • License: LGPL (
      The tool includes two pipelines: one using the ARCOMEM sentiment detection software supplied complete, and one using the
      SentiStrength tool (better results) but it is missing the relevant jar which cannot be distributed by SENSEI.)
    • Open source: yes
    • Programming languages: java, groovy, jape
    • Repository integration: yes
    • Dependencies: GATE, ARCOMEM or SentiStrength
    • URL: http://www.dcs.shef.ac.uk/~adam/stuff/sensei/sensei-USFD-gate-pipelines.zip
  • Social media eval prototype: This module contains the evaluation UI for the social media use case.
  • ACOF tool: This module provides an annotation interface for Agent Conversation Observation Form (ACOF) and support for the extrinsic evaluation.
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The research leading to these results has received funding from the European Union - Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 610916 – SENSEI.