Triple

T1736398
Position Surface form Disambiguated ID Type / Status
Subject Pierre de Coubertin E37928 entity
Predicate placeOfBirth P1 FINISHED
Object Paris, France E568 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: Paris, France | Statement: [Pierre de Coubertin, placeOfBirth, Paris, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris, France
Context triple: [Pierre de Coubertin, placeOfBirth, Paris, France]
  • A. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • B. Paris
    Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
  • C. Fontainebleau, France
    Fontainebleau, France is a historic town southeast of Paris best known for its vast forest and royal château, long associated with French monarchs and outdoor recreation.
  • D. Neuilly-sur-Seine, France
    Neuilly-sur-Seine, France is an affluent suburban commune just west of central Paris, known for its high standard of living and status as one of the wealthiest areas in the country.
  • E. Palaiseau
    Palaiseau is a suburban commune in the southern outskirts of Paris, France, known for hosting major scientific and engineering institutions.
  • 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_69a8861cc6ac8190ac0b2e31ccf62851 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63a369048190bae352573f5082f1 completed March 6, 2026, 5:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8abe91bc8190ba363e1f7fd07b9f completed March 8, 2026, 2:42 p.m.
Created at: March 4, 2026, 7:30 p.m.