Triple

T507427
Position Surface form Disambiguated ID Type / Status
Subject Hollis Hall E10530 entity
Predicate hasNotableResident P1092 FINISHED
Object Matt Damon E6366 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: Matt Damon | Statement: [Hollis Hall, hasNotableResident, Matt Damon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Damon
Context triple: [Hollis Hall, hasNotableResident, Matt Damon]
  • A. Matt Damon chosen
    Matt Damon is an American actor, producer, and screenwriter known for his versatile performances in films such as Good Will Hunting, the Bourne series, and The Martian.
  • B. Ben Affleck
    Ben Affleck is an American actor, director, and screenwriter known for films such as "Good Will Hunting," "Argo," and for portraying Batman in the DC Extended Universe.
  • C. George Clooney
    George Clooney is an American actor, filmmaker, and activist renowned for his work in film and television as well as his humanitarian and political advocacy.
  • D. Brad Pitt
    Brad Pitt is an American actor and film producer renowned for his leading roles in major Hollywood films and for winning multiple Academy Awards.
  • E. Leonardo DiCaprio
    Leonardo DiCaprio is an Academy Award–winning American actor and environmental activist known for his roles in films like Titanic, Inception, and The Revenant, as well as his prominent climate advocacy.
  • 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_69a2e848adf881908e5e04f7af030093 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f14dcd688190ad47a3b31b95b6d4 completed Feb. 28, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a498506418819090190a35e8763982 completed March 1, 2026, 7:49 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.