Triple

T14691178
Position Surface form Disambiguated ID Type / Status
Subject The Bastard Executioner E345036 entity
Predicate starredActor P5563 FINISHED
Object Danny Sapani E736138 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: Danny Sapani | Statement: [The Bastard Executioner, starredActor, Danny Sapani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danny Sapani
Context triple: [The Bastard Executioner, starredActor, Danny Sapani]
  • A. Danny Sapani chosen
    Danny Sapani is a British-Ghanaian actor known for his work in film, television, and theatre, including roles in projects like "Penny Dreadful," "Black Panther," and "Star Wars: The Last Jedi."
  • B. Jonathan Benassaya
    Jonathan Benassaya is a French entrepreneur best known for co-founding the music streaming service Deezer.
  • C. Phil Pinto
    Phil Pinto is a music video director known for his work on high-profile pop and R&B projects, including Bruno Mars’s “It Will Rain.”
  • D. Dan Pinto
    Dan Pinto is a fictional character portrayed by O’Shea Jackson Jr., best known as the charismatic and supportive love interest in the film "Ingrid Goes West."
  • E. Nick Mehta
    Nick Mehta is a technology executive best known as the CEO of Gainsight and a prominent advocate and thought leader in the field of customer success.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb585d46c81908d6964130914cec4 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde18b4bdc8190b5daf05484de7cd8 completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:28 a.m.