Triple

T1180979
Position Surface form Disambiguated ID Type / Status
Subject The Beaver E25135 entity
Predicate starring P1507 FINISHED
Object Jennifer Lawrence E25705 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: Jennifer Lawrence | Statement: [The Beaver, starring, Jennifer Lawrence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer Lawrence
Context triple: [The Beaver, starring, Jennifer Lawrence]
  • A. Jennifer Lawrence chosen
    Jennifer Lawrence is an American actress acclaimed for her versatile performances in films such as "Silver Linings Playbook" and "The Hunger Games" series.
  • B. Kristen Stewart
    Kristen Stewart is an American actress best known for her role as Bella Swan in the "Twilight" film series and for her acclaimed performances in independent and arthouse films.
  • C. Mia Wasikowska
    Mia Wasikowska is an Australian actress known for her versatile performances in films such as "Alice in Wonderland," "Jane Eyre," and various independent dramas.
  • D. Emmy Rossum
    Emmy Rossum is an American actress and singer best known for her role as Fiona Gallagher on the TV series "Shameless" and for her work in films such as "The Phantom of the Opera."
  • E. Rooney Mara
    Rooney Mara is an American actress known for her acclaimed performances in films such as "The Girl with the Dragon Tattoo" and "Carol."
  • 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_69a494267b4c819088c97a59182bf56a completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd32c5f48190b4e2d39fa052cbb7 completed March 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac99775ca081909e4d8c81c40c277b completed March 7, 2026, 9:32 p.m.
Created at: March 1, 2026, 7:45 p.m.