team

Camille Roth
Camille Roth
  • Research director
  • Formalization
Telmo Menezes
Telmo Menezes
  • Research
  • Technical architecture
  • Neuro-symbolic modeling
Florian Schmitt
Florian Schmitt
  • UX / UI Design
  • Ergonomic interface design
  • Front-end integration

project origin

context and challenges

illustration Information management
Information management

spreadsheets, relational databases

illustration Information extraction
Information extraction

turning text into structured data

illustration Desire for automation
Desire for automation

AI boom raised organizational awareness

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outstanding needs

  • Lack of internal AI expertise
  • Difficulty in evaluating or negotiating services
  • Solutions not tailored to specific needs
  • Uncertain cost-benefit analysis
  • Lack of trust in LLMs
  • Hallucinations, opacity

interface between two canonical approaches

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symbolic rules

explicit specification of target regularities

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  • High precision
  • Low recall
  • Explainable
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  • Rigid
  • Requires few
    examples

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deep learning, LLMs

implicitly captures regularities with numerous annotated examples

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  • High recall
  • Enhanced handling
    of context
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  • Black box
  • Costly training
  • Limited ability to
    explore data

hyperquest

best of both worlds

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HyperQuest
reveals key patterns

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Allows domain experts without AI expertise to select the most relevant cases

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Suggests/co-constructs targeted information extraction rules with few examples

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Expands assisted extraction through neuro-symbolic patterns

successive refinement of sub-corpora and increasingly relevant patterns

partners


partly funded by ERC Proof-of-Concept
grant « HyperQuest » #101292712

do you want to know more?

If you have any questions about the project or would like to get in touch with us, we would be pleased to hear from you.

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