Triple

T14944034
Position Surface form Disambiguated ID Type / Status
Subject The Wind and the Lion E372605 entity
Predicate editedBy P1954 FINISHED
Object Tom Rolf E214378 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: Tom Rolf | Statement: [The Wind and the Lion, editedBy, Tom Rolf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Rolf
Context triple: [The Wind and the Lion, editedBy, Tom Rolf]
  • A. Tom Rolf chosen
    Tom Rolf was an American film editor best known for his work on acclaimed movies such as "Taxi Driver" and for winning an Academy Award for editing "The Right Stuff."
  • B. Ben Rolf
    Ben Rolf is a character in the horror novel and film "Burnt Offerings," known as the young son in the family that moves into a sinister, transformative mansion.
  • C. David Rolf
    David Rolf is a fictional character from the horror novel and film "Burnt Offerings," involved in the story’s unsettling, supernatural events surrounding a sinister summer rental house.
  • D. Bob Rolontz
    Bob Rolontz was an American record producer and music industry executive best known for his influential work in early rock and roll and rhythm and blues.
  • E. Ron Hagen
    Ron Hagen is a cinematographer best known for his work on the Australian film "Romper Stomper."
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded68d20048190a403af85fe43dede completed April 15, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e9484e8819086ca6a59d672e49d completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 2:38 a.m.