Triple

T22254724
Position Surface form Disambiguated ID Type / Status
Subject Zulu E550067 entity
Predicate hasHistoricalInaccuracies P36343 FINISHED
Object yes LITERAL 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: yes | Statement: [Zulu, hasHistoricalInaccuracies, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasHistoricalInaccuracies
Context triple: [Zulu, hasHistoricalInaccuracies, yes]
  • A. historicalAccuracyOfPopularDepictions chosen
    Indicates how faithfully popular portrayals or representations reflect the actual historical events, conditions, or figures they depict.
  • B. hasUncertainHistoricBasis
    Indicates that the historical foundation or authenticity of the related fact, event, or relationship is doubtful, disputed, or not firmly established.
  • C. hasHistoricalReliability
    Indicates that something is supported by credible historical evidence and is considered trustworthy as an account of past events.
  • D. hasHistoricalContext
    Indicates that something is related to, influenced by, or best understood in light of specific past events, conditions, or time periods.
  • E. hasHistoricity
    Indicates that something possesses historical existence, significance, or authenticity, rather than being purely fictional, mythical, or timeless.
  • F. None of above.

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_69e11e42adb8819087714772ea606709 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f138c1d70881908df47b0f818c0022 completed April 28, 2026, 10:46 p.m.
PD Predicate disambiguation batch_69e72fe1e0cc8190bd13cff2a0846225 completed April 21, 2026, 8:05 a.m.
Created at: April 16, 2026, 8:39 p.m.