Triple

T1800424
Position Surface form Disambiguated ID Type / Status
Subject Galactic Empire series E39704 entity
Predicate alsoKnownAs P39 FINISHED
Object Empire series E201009 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: Empire series | Statement: [Galactic Empire series, alsoKnownAs, Empire series]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Empire series
Context triple: [Galactic Empire series, alsoKnownAs, Empire series]
  • A. Empire series chosen
    The Empire series is a set of early science fiction novels by Isaac Asimov that explore a future Galactic Empire and form part of the larger universe linking his Robot and Foundation stories.
  • B. Empire
    Empire is a popular American musical drama television series that follows the power struggles and family dynamics within a hip-hop music and entertainment company.
  • C. Empire
    Empire is Andy Warhol’s 1964 avant-garde experimental film consisting of an extended, stationary shot of the Empire State Building, notable for its extreme duration and minimalist style.
  • D. Empire
    Empire is a small unincorporated community located in Stanislaus County in California’s Central Valley.
  • E. Empire
    Empire is a post-exploitation and command-and-control framework commonly used for penetration testing and red team operations.
  • 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_69a88632aa588190ba3978fde0db5bbd completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa656ad5d4819090e677ad137b0cd1 completed March 6, 2026, 5:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf5645808190a774d96cfe5c5e58 completed March 8, 2026, 6:26 p.m.
Created at: March 4, 2026, 7:32 p.m.