Triple

T16140245
Position Surface form Disambiguated ID Type / Status
Subject Calacuccia E391633 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: [Calacuccia, officialLanguage, French]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: French
Context triple: [Calacuccia, officialLanguage, French]
  • A. French
    French is a common English-language surname of French origin borne by various notable individuals, including philanthropist Melinda Ann French (Melinda Gates).
  • B. 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.
  • 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_69d87f1bb0988190b490d273dbf3fd03 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21a07b7908190b4e1ec57f60a9274 completed April 17, 2026, 11:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff2b75988819094baaff8f53f48ce completed May 10, 2026, 2:51 a.m.
Created at: April 10, 2026, 5:01 a.m.