Triple

T8529004
Position Surface form Disambiguated ID Type / Status
Subject William John Neeson E201894 entity
Predicate alsoKnownAs P39 FINISHED
Object Liam Neeson E34013 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: Liam Neeson | Statement: [William John Neeson, alsoKnownAs, Liam Neeson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liam Neeson
Context triple: [William John Neeson, alsoKnownAs, Liam Neeson]
  • A. Liam Neeson chosen
    Liam Neeson is an Irish actor renowned for his powerful performances in dramas and action films, including roles in "Schindler's List," "Taken," and "Star Wars: Episode I – The Phantom Menace."
  • B. Sean Brosnan
    Sean Brosnan is an American actor and filmmaker, best known as the son of Irish actor Pierce Brosnan.
  • C. Paris Brosnan
    Paris Brosnan is an American model and filmmaker, best known as the son of actor Pierce Brosnan and for his work in fashion and humanitarian projects.
  • D. Stephen Lang
    Stephen Lang is an American actor known for his intense character roles in film, television, and theater, including prominent performances in movies like "Avatar" and "Public Enemies."
  • E. Bob Hoskins
    Bob Hoskins was an acclaimed English actor known for his intense, often gritty performances in films such as "The Long Good Friday," "Mona Lisa," and "Who Framed Roger Rabbit."
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe672e0588190a84328e1bf974f08 completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d5e5b58819095c1c915dfe27b52 completed April 2, 2026, 1:21 p.m.
Created at: March 30, 2026, 6:17 p.m.