Triple

T18950127
Position Surface form Disambiguated ID Type / Status
Subject Alliances for Innovation E463623 entity
Predicate predecessor P97 FINISHED
Object Knowledge Alliances NE NERFINISHED

How this triple was built (3 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Knowledge Alliances | Statement: [Alliances for Innovation, predecessor, Knowledge Alliances]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Knowledge Alliances
Context triple: [Alliances for Innovation, predecessor, Knowledge Alliances]
  • A. Knowledge Transfer Partnerships
    Knowledge Transfer Partnerships are a UK-wide scheme that links businesses with academic or research institutions to drive innovation and improve competitiveness through collaborative projects.
  • B. Knowledge Capital
    Knowledge Capital is a large-scale innovation and creative hub in Osaka that brings together businesses, researchers, and the public for exhibitions, labs, and collaborative projects.
  • C. Knowledge Services Group
    Knowledge Services Group is a division within the Congressional Research Service that focuses on managing, organizing, and providing access to information and knowledge resources for Congress.
  • D. Knowledge Corridor
    The Knowledge Corridor is a passenger rail route in western Massachusetts and northern Connecticut that serves major educational and research centers along the Connecticut River Valley.
  • E. alliances for innovation
    Alliances for Innovation are Erasmus+ funding actions that support strategic partnerships between higher education institutions, vocational education providers, and businesses to foster innovation, skills development, and cooperation across Europe.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Knowledge Alliances
Target entity description: Knowledge Alliances were European higher education–business cooperation projects under the Erasmus+ programme, aimed at fostering innovation, entrepreneurship, and skills development through cross-sector partnerships.
  • A. Knowledge Transfer Partnerships
    Knowledge Transfer Partnerships are a UK-wide scheme that links businesses with academic or research institutions to drive innovation and improve competitiveness through collaborative projects.
  • B. Knowledge Capital
    Knowledge Capital is a large-scale innovation and creative hub in Osaka that brings together businesses, researchers, and the public for exhibitions, labs, and collaborative projects.
  • C. Knowledge Services Group
    Knowledge Services Group is a division within the Congressional Research Service that focuses on managing, organizing, and providing access to information and knowledge resources for Congress.
  • D. Knowledge Corridor
    The Knowledge Corridor is a passenger rail route in western Massachusetts and northern Connecticut that serves major educational and research centers along the Connecticut River Valley.
  • E. alliances for innovation chosen
    Alliances for Innovation are Erasmus+ funding actions that support strategic partnerships between higher education institutions, vocational education providers, and businesses to foster innovation, skills development, and cooperation across Europe.
  • F. None of above.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8dcfec90481909e926be9767e5779 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d542b238819089ccd2df279a2f7f completed April 20, 2026, 7:26 a.m.
Created at: April 10, 2026, noon