Triple

T22357664
Position Surface form Disambiguated ID Type / Status
Subject Royal Society Science Book Prize E552695 entity
Predicate sponsor P67 FINISHED
Object Aventis NE NERFINISHED

How this triple was built (2 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: Aventis | Statement: [Royal Society Science Book Prize, sponsor, Aventis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aventis
Context triple: [Royal Society Science Book Prize, sponsor, Aventis]
  • A. Sanofi chosen
    Sanofi is a major French multinational pharmaceutical company known for developing prescription medicines, vaccines, and consumer healthcare products worldwide.
  • B. Roche
    Roche is a major Swiss multinational healthcare company and one of the world’s leading pharmaceutical and diagnostics firms.
  • C. Roche
    Roche is a common surname of French origin borne by various notable individuals across fields such as architecture, politics, and the arts.
  • D. Roche
    Roche is a village and civil parish in Cornwall, England, known for its distinctive granite outcrop and historic chapel perched on Roche Rock.
  • E. Rhône-Poulenc Rorer
    Rhône-Poulenc Rorer was a major French-American pharmaceutical company known for developing important cancer therapies and later becoming part of Sanofi through mergers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69e11e4a0ad08190a385b4d343cf6524 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f157d1a87c8190a3e195cfbbb0d64f completed April 29, 2026, 12:58 a.m.
Created at: April 16, 2026, 8:44 p.m.