Triple

T13313481
Position Surface form Disambiguated ID Type / Status
Subject French theatre E317131 entity
Predicate hasLanguage P15 FINISHED
Object French language E13984 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: French language | Statement: [French theatre, hasLanguage, French language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: French language
Context triple: [French theatre, hasLanguage, French language]
  • A. French chosen
    French is a Romance language that evolved from Latin and is now spoken worldwide as both a native and official language in many countries.
  • B. French
    French is a common English-language surname of French origin borne by various notable individuals, including philanthropist Melinda Ann French (Melinda Gates).
  • C. Louis (French)
    Louis is the French given name corresponding to the name Ludwik in other languages.
  • D. French Wikiversity
    French Wikiversity is the French-language edition of Wikiversity, a Wikimedia project dedicated to free educational resources and collaborative learning.
  • E. French Corner
    French Corner is the English meaning of the name "Franschhoek," a South African town historically settled by French Huguenots.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990f6d34c8190ba19dc2df7d42c22 completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716ec2ec08190a6e37795b422fe71 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:29 p.m.