Triple

T4303474
Position Surface form Disambiguated ID Type / Status
Subject Georges Picquart E99896 entity
Predicate givenName P17 FINISHED
Object Georges E18182 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: Georges | Statement: [Georges Picquart, givenName, Georges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Georges
Context triple: [Georges Picquart, givenName, Georges]
  • A. Georges chosen
    Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
  • B. Jacques
    Jacques is the French form of the given name James, commonly used in French-speaking countries.
  • C. Pierre
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • D. Eugène
    Eugène is a masculine given name of French origin, derived from the Greek "Eugenios," meaning "well-born" or "noble."
  • E. Théodore
    Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b350b792608190ac778b79c740256a completed March 12, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd569f30088190bdc9ea72fe35be35 completed March 20, 2026, 2:15 p.m.
Created at: March 12, 2026, 11:08 p.m.