Triple

T3783773
Position Surface form Disambiguated ID Type / Status
Subject Battleship E85477 entity
Predicate starredActor P5563 FINISHED
Object Taylor Kitsch E342944 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: Taylor Kitsch | Statement: [Battleship, starredActor, Taylor Kitsch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taylor Kitsch
Context triple: [Battleship, starredActor, Taylor Kitsch]
  • A. Taylor Kitsch chosen
    Taylor Kitsch is a Canadian actor best known for his breakout role as Tim Riggins on the television series "Friday Night Lights" and for starring in films such as "John Carter" and "Lone Survivor."
  • B. Garrett Hedlund
    Garrett Hedlund is an American actor and singer known for roles in films such as "Tron: Legacy," "Friday Night Lights," and "Country Strong."
  • C. James Marsden
    James Marsden is an American actor known for his roles in films like the X-Men series, Enchanted, and Hairspray, as well as prominent television work.
  • D. Ethan Embry
    Ethan Embry is an American actor known for his roles in 1990s films such as "Empire Records," "Can't Hardly Wait," and various television series.
  • E. Jake Gyllenhaal
    Jake Gyllenhaal is an acclaimed American actor known for his intense, versatile performances in films ranging from independent dramas to major studio thrillers.
  • 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_69aed937fa8881908208ef3801060826 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee3dc6590819098dda08206206612 completed March 9, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f04747448190be484cda5b2a7a8c completed March 14, 2026, 5:21 a.m.
Created at: March 9, 2026, 3:13 p.m.