Triple

T14200214
Position Surface form Disambiguated ID Type / Status
Subject Constitution of Djibouti E351943 entity
Predicate definesOfficialLanguage P236 FINISHED
Object French 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 | Statement: [Constitution of Djibouti, definesOfficialLanguage, French]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: French
Context triple: [Constitution of Djibouti, definesOfficialLanguage, French]
  • 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. FR
    FR is the vehicle registration code for the Freiburg im Breisgau district in the German state of Baden-Württemberg.
  • E. FR
    FR is the Swiss vehicle registration code for the canton of Fribourg.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61f472548190a1a7edc40526eac3 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd194f13688190af7ef5ceb92a73ff completed May 7, 2026, 10:59 p.m.
Created at: April 10, 2026, 1:04 a.m.