Triple

T10122700
Position Surface form Disambiguated ID Type / Status
Subject Maryann Brandon E223333 entity
Predicate hasWorkedWithDirector P19638 FINISHED
Object Ruben Fleischer E317575 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: Ruben Fleischer | Statement: [Maryann Brandon, hasWorkedWithDirector, Ruben Fleischer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ruben Fleischer
Context triple: [Maryann Brandon, hasWorkedWithDirector, Ruben Fleischer]
  • A. Ruben Fleischer chosen
    Ruben Fleischer is an American film director and producer best known for helming movies such as "Zombieland," "Venom," and other major Hollywood action-comedies.
  • B. Peyton Reed
    Peyton Reed is an American film director known for helming major studio comedies and Marvel superhero films, including entries in the Ant-Man series.
  • C. Tim Miller
    Tim Miller is a filmmaker best known for directing the blockbuster science fiction film "Deadpool" and later helming "Terminator: Dark Fate."
  • D. Will Speck
    Will Speck is an American film director best known for co-directing mainstream comedies such as "Blades of Glory" and "Office Christmas Party."
  • E. David Slade
    David Slade is a British film and television director known for his work in horror and thriller genres, including films like "Hard Candy," "30 Days of Night," and "The Twilight Saga: Eclipse."
  • 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_69ca8422047c81909d66b717b8b18cf3 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd26846b8819098594bf211920eb2 completed April 2, 2026, 2:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e5b6101081909c97956591b01af9 completed April 5, 2026, 10:44 p.m.
Created at: March 30, 2026, 9:05 p.m.