Triple

T5515054
Position Surface form Disambiguated ID Type / Status
Subject The Star E144660 entity
Predicate starring P1507 FINISHED
Object Warner Anderson E493392 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: Warner Anderson | Statement: [The Star, starring, Warner Anderson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warner Anderson
Context triple: [The Star, starring, Warner Anderson]
  • A. Warner Anderson chosen
    Warner Anderson was an American film and television actor active from the 1930s to the 1970s, known for his character roles in dramas and crime stories.
  • B. Walt Anderson
    Walt Anderson is a former NFL official who served as a longtime referee and later became the league’s senior vice president of officiating.
  • C. Roy Anderson
    Roy Anderson is a British epidemiologist and academic leader known for his influential work in infectious disease modeling and his tenure heading major scientific institutions.
  • D. Harlan Anderson
    Harlan Anderson was an American engineer and entrepreneur best known as a co-founder of the pioneering minicomputer company Digital Equipment Corporation (DEC).
  • E. Kenneth Anderson
    Kenneth Anderson was a British Army general best known for leading Allied ground forces in the North African campaign during World War II, including the early phases of the Tunisian campaign.
  • 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_69c008f77ff88190b0cd50ca207295d1 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f5b4e988190b590b4157cf089c1 completed March 22, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04cc0735881909b7ea6909570a750 completed March 22, 2026, 8:10 p.m.
Created at: March 22, 2026, 3:33 p.m.