Triple

T13483509
Position Surface form Disambiguated ID Type / Status
Subject Ian Baker E318433 entity
Predicate workedOn P3 FINISHED
Object Barbarosa E844141 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: Barbarosa | Statement: [Ian Baker, workedOn, Barbarosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barbarosa
Context triple: [Ian Baker, workedOn, Barbarosa]
  • A. Barbarosa chosen
    Barbarosa is a 1982 Western film, written by William D. Wittliff and starring Willie Nelson and Gary Busey, known for its blend of folklore, moral ambiguity, and character-driven storytelling.
  • B. Etzel
    Etzel is the powerful king of the Huns in the medieval German epic "Nibelungenlied," a figure based on the historical Attila the Hun.
  • C. Etzel
    Etzel was a Zionist paramilitary organization that operated in Mandatory Palestine before the establishment of the State of Israel.
  • D. Günther
    Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
  • E. Günther
    Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf3868ec8190a6a1803018d4f2d8 completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7463715dc8190a70a17b3ea661006 completed May 3, 2026, 12:57 p.m.
Created at: April 9, 2026, 9:42 p.m.