Triple

T2778334
Position Surface form Disambiguated ID Type / Status
Subject Matilda E61630 entity
Predicate hasUnrequitedLoveFor P7325 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: [Matilda, hasUnrequitedLoveFor, Theodore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Theodore
Context triple: [Matilda, hasUnrequitedLoveFor, 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 given name of Benjamin "Bugsy" Siegel, the notorious American mobster who played a key role in the development of Las Vegas.
  • 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_69ab4b7e43c48190997b8fc8fb1663ab completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd83c5fc8190936b971d5577d3f9 completed March 7, 2026, 8:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc64f94208190b9b8da1fdf6252cc completed March 10, 2026, 7:20 a.m.
Created at: March 6, 2026, 9:57 p.m.