Triple

T18658820
Position Surface form Disambiguated ID Type / Status
Subject Tabarchin E456135 entity
Predicate hasLexicalBorrowingFrom P1754 FINISHED
Object French NE NERFINISHED

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: [Tabarchin, hasLexicalBorrowingFrom, French]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: French
Context triple: [Tabarchin, hasLexicalBorrowingFrom, 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. Free French
    Free French was the World War II movement led by Charles de Gaulle that continued the fight against Axis powers after France’s 1940 defeat and formed the basis of the postwar French government.
  • E. Louis (French)
    Louis is the French given name corresponding to the name Ludwik in other languages.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38ea1e88190997e9b231190ba6f completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55087ae8081909cb4c0ce6c809d55 completed April 19, 2026, 10 p.m.
Created at: April 10, 2026, 11:48 a.m.