Triple

T1637189
Position Surface form Disambiguated ID Type / Status
Subject The Polar Express E35382 entity
Predicate starred P5563 FINISHED
Object Daryl Sabara E73071 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: Daryl Sabara | Statement: [The Polar Express, starred, Daryl Sabara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daryl Sabara
Context triple: [The Polar Express, starred, Daryl Sabara]
  • A. Daryl Sabara chosen
    Daryl Sabara is an American actor best known for playing Juni Cortez in the Spy Kids film series.
  • B. Paul Wall
    Paul Wall is an American rapper and DJ from Houston, Texas, known for his Southern hip hop style and association with the city’s chopped and screwed scene.
  • C. Craig Bierko
    Craig Bierko is an American actor known for his work in film, television, and theater, often playing charismatic or villainous roles.
  • D. Robby Mook
    Robby Mook is an American political strategist best known for serving as campaign manager for Hillary Clinton’s 2016 U.S. presidential campaign.
  • E. Travis Banton
    Travis Banton was a prominent American Hollywood costume designer best known for his glamorous, influential work at Paramount Pictures during the 1920s and 1930s.
  • 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_69a886036bc081909ff5de16dbe5e8ea completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a192d588190bbfa4693ed787c05 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad6099979481908e2c506323d546dd completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:28 p.m.