Triple

T11087265
Position Surface form Disambiguated ID Type / Status
Subject Jean Theodore Keteleer E262153 entity
Predicate hasGivenName P17 FINISHED
Object Theodore E55214 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: Theodore | Statement: [Jean Theodore Keteleer, hasGivenName, Theodore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Theodore
Context triple: [Jean Theodore Keteleer, hasGivenName, Theodore]
  • A. Theodore chosen
    Theodore is a masculine given name of Greek origin, meaning "gift of God," from which the nickname Ted is derived.
  • B. Theodor
    Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
  • C. Theodor
    Theodor is the given name of Emil Theodor Kocher, a Swiss surgeon and Nobel laureate renowned for his pioneering work in thyroid surgery.
  • D. Theodore Reeves
    Theodore Reeves was a screenwriter best known for his work on classic Hollywood films, including the beloved horse-racing drama "National Velvet."
  • E. Benjamin
    Benjamin is the naive, dream-filled protagonist of Mendele Mocher Sforim’s satirical Yiddish novel "The Travels of Benjamin the Third," often likened to a Jewish Don Quixote.
  • 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799c5008081908f59612243fa4f7a completed April 9, 2026, 12:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7a6dfa8819096f822294eb64dd1 completed April 18, 2026, 8:20 p.m.
Created at: April 8, 2026, 9:27 p.m.