Triple

T2559535
Position Surface form Disambiguated ID Type / Status
Subject Nicolas Sarkozy E57209 entity
Predicate givenName P17 FINISHED
Object Nicolas E28979 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: Nicolas | Statement: [Nicolas Sarkozy, givenName, Nicolas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nicolas
Context triple: [Nicolas Sarkozy, givenName, Nicolas]
  • A. Nicholas chosen
    Nicholas is a masculine given name of Greek origin, commonly used in many cultures and historically borne by numerous saints, rulers, and notable figures.
  • B. Pierre
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • C. Jacques
    Jacques is the French form of the given name James, commonly used in French-speaking countries.
  • D. Phillippe
    Phillippe is a given name and surname, typically a French-influenced variant of Philip, used for both real and fictional individuals.
  • E. René
    René is a French given name commonly used for males and historically associated with several notable figures in politics, arts, and philosophy.
  • 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_69ab4a4ef9008190a0e6d4422b9418b7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd333370c8190b1d64ec99e999913 completed March 7, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5d2061108190b6250d2943736ae4 completed March 9, 2026, 11:52 p.m.
Created at: March 6, 2026, 9:48 p.m.