Triple

T10148882
Position Surface form Disambiguated ID Type / Status
Subject William D. Wittliff E232578 entity
Predicate wroteScreenplayFor P15305 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: [William D. Wittliff, wroteScreenplayFor, Barbarosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barbarosa
Context triple: [William D. Wittliff, wroteScreenplayFor, 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 was a Zionist paramilitary organization that operated in Mandatory Palestine before the establishment of the State of Israel.
  • C. Günther
    Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
  • D. Günther
    Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
  • E. Schwartzerdt
    Schwartzerdt is the original German surname of the 16th-century Protestant reformer and humanist Philip Melanchthon, which he later Hellenized into the name by which he is best known.
  • 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_69ca84885e48819088a31b127cf44904 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec024da481908b8170fcf3b18e67 completed April 2, 2026, 4:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3009992388190ab2a4aee23d0e004 completed April 6, 2026, 12:38 a.m.
Created at: March 30, 2026, 9:08 p.m.