Triple

T12728924
Position Surface form Disambiguated ID Type / Status
Subject Corton-Charlemagne E304178 entity
Predicate regulatingBody P86 FINISHED
Object INAO E49242 NE FINISHED

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: INAO | Statement: [Corton-Charlemagne, regulatingBody, INAO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: INAO
Context triple: [Corton-Charlemagne, regulatingBody, INAO]
  • A. INAO chosen
    INAO (Institut National de l’Origine et de la Qualité) is the French governmental organization responsible for overseeing and protecting appellations of origin and quality labels for agricultural products, including wine.
  • B. IAO
    IAO is the abbreviation for the Fraunhofer Institute for Industrial Engineering, a German research institute focused on applied industrial and organizational engineering.
  • C. INACH
    INACH is Chile’s national Antarctic research institute responsible for coordinating and promoting the country’s scientific activities and presence in Antarctica.
  • D. INAIL
    INAIL is the Italian National Institute for Insurance against Accidents at Work, responsible for managing mandatory workplace injury insurance and promoting occupational safety and prevention.
  • E. INEA
    INEA is a Brazilian environmental agency responsible for managing and protecting natural resources and ecosystems in the state of Rio de Janeiro.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d964172490819080cd022ff8290b6e completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c841edc81909147d30c51471c47 completed May 2, 2026, 10:36 p.m.
Created at: April 9, 2026, 5:25 p.m.