Triple

T17197593
Position Surface form Disambiguated ID Type / Status
Subject Vanuatu government E417392 entity
Predicate officialLanguage 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: [Vanuatu government, officialLanguage, French]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: French
Context triple: [Vanuatu government, officialLanguage, 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. Franzese
    Franzese is an Italian surname borne by various notable individuals in fields such as entertainment and organized crime.
  • D. Louis (French)
    Louis is the French given name corresponding to the name Ludwik in other languages.
  • E. FR
    FR is the vehicle registration code for the Freiburg im Breisgau district in the German state of Baden-Württemberg.
  • 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_69d886d6ba8c819093215917b3d01689 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42dab718c8190b6f5b08189cf2eb2 completed April 19, 2026, 1:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a015fd7ef048190b0828ec6ea0e119c completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:38 a.m.