Triple

T6808749
Position Surface form Disambiguated ID Type / Status
Subject Wyatt Morgan Cooper E156575 entity
Predicate hasParent P120 FINISHED
Object Benjamin Maisani E195828 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: Benjamin Maisani | Statement: [Wyatt Morgan Cooper, hasParent, Benjamin Maisani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Benjamin Maisani
Context triple: [Wyatt Morgan Cooper, hasParent, Benjamin Maisani]
  • A. Benjamin Maisani chosen
    Benjamin Maisani is a French-born nightclub owner and businessman best known as the longtime partner of American journalist Anderson Cooper.
  • B. Jonathan Benassaya
    Jonathan Benassaya is a French entrepreneur best known for co-founding the music streaming service Deezer.
  • C. Paul Ben-Haim
    Paul Ben-Haim was a prominent German-born Israeli composer and conductor, known as a pioneer of Israeli art music who blended Western classical traditions with Middle Eastern and Jewish musical elements.
  • D. Benjamin Ettenberg
    Benjamin Ettenberg is a charming, intellectually sharp doctor who becomes a significant romantic interest for Midge in the television series "The Marvelous Mrs. Maisel."
  • E. Benjamin Kanes
    Benjamin Kanes is an American actor and filmmaker known for supporting roles in film and television, including appearances in projects like "The Visit."
  • 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_69c68828b26c819090fe9df7612bbc27 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d30b56c48190a5b244ea7e0c669a completed March 27, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71aa5411c81908d05bef3213b39f1 completed March 28, 2026, 12:02 a.m.
Created at: March 27, 2026, 2:16 p.m.