Triple

T6600072
Position Surface form Disambiguated ID Type / Status
Subject The Vagabond E148573 entity
Predicate featuresActor P15562 FINISHED
Object Frank J. Coleman E800274 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: Frank J. Coleman | Statement: [The Vagabond, featuresActor, Frank J. Coleman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frank J. Coleman
Context triple: [The Vagabond, featuresActor, Frank J. Coleman]
  • A. Frank J. Coleman chosen
    Frank J. Coleman was an American silent film actor known for appearing in numerous early comedies, including several Charlie Chaplin films.
  • B. Joseph P. Kerwin
    Joseph P. Kerwin is an American physician and former NASA astronaut who became the first medical doctor in space as a crew member aboard the Skylab space station.
  • C. Thomas R. Cornelius
    Thomas R. Cornelius was an American pioneer and politician in Oregon, known for his role in the region’s early settlement and development.
  • D. John A. Crews
    John A. Crews was a United States military service member interred at Golden Gate National Cemetery, likely recognized for his service to the country.
  • E. Charles Coleman
    Charles Coleman was an Australian-born character actor known for his frequent roles as butlers and valets in numerous Hollywood films during the early to mid-20th century.
  • 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_69c687e7b8688190811ffee72e096468 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aef36b308190a172f0396e337309 completed March 27, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12cabbb088190bada143db831c466 completed April 4, 2026, 3:22 p.m.
Created at: March 27, 2026, 1:56 p.m.