Triple

T13324450
Position Surface form Disambiguated ID Type / Status
Subject The Seventh Cross E317400 entity
Predicate narrator P2181 FINISHED
Object Ray Collins E108489 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: Ray Collins | Statement: [The Seventh Cross, narrator, Ray Collins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ray Collins
Context triple: [The Seventh Cross, narrator, Ray Collins]
  • A. Ray Collins chosen
    Ray Collins was an American character actor best known for his roles in classic films and radio, including his appearance in Orson Welles’s landmark film "Citizen Kane."
  • B. Alan Collins
    Alan Collins was a British-born sculptor known for his modernist religious and commemorative works, including prominent public memorials in the United States and the United Kingdom.
  • C. Andy Collins
    Andy Collins is a cinematographer best known for his work on the British film "Brassed Off."
  • D. Roy Marples
    Roy Marples is a software engineer best known for his work on the OpenRC init system and various networking tools in the Linux and BSD ecosystems.
  • E. Colin Blakely
    Colin Blakely was a Northern Irish character actor known for his powerful stage work and memorable supporting roles in British and international films of the 1960s–1980s.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9992c1fec8190bcb6a6bb3c973a24 completed April 11, 2026, 12:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69f74612bab88190bf1a895b87be12c1 completed May 3, 2026, 12:56 p.m.
Created at: April 9, 2026, 9:30 p.m.