Triple

T114400
Position Surface form Disambiguated ID Type / Status
Subject Beijing E2312 entity
Predicate timeZone P109 FINISHED
Object China Standard Time E5773 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: China Standard Time | Statement: [Beijing, timeZone, China Standard Time]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: China Standard Time
Context triple: [Beijing, timeZone, China Standard Time]
  • A. China Standard Time chosen
    China Standard Time is the single official time zone used throughout mainland China, corresponding to UTC+8.
  • B. Japan Standard Time
    Japan Standard Time is the standard time zone used throughout Japan, set at nine hours ahead of Coordinated Universal Time (UTC+9) without daylight saving time.
  • C. Indian Standard Time
    Indian Standard Time is the time zone used throughout India, set at UTC+5:30.
  • D. Cuba Standard Time
    Cuba Standard Time is the standard time zone used throughout the island nation of Cuba, typically corresponding to UTC−05:00.
  • E. Central European Time
    Central European Time is a standard time zone used by many countries in central and western Europe, typically one hour ahead of Coordinated Universal Time (UTC+1).
  • 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_69a24fcdaeb48190a2d796677e4b3281 completed Feb. 28, 2026, 2:15 a.m.
NER Named-entity recognition batch_69a256effaac81908c22be65d9f668a4 completed Feb. 28, 2026, 2:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69a27c0652508190aa8d569ee7dae7bc completed Feb. 28, 2026, 5:24 a.m.
Created at: Feb. 28, 2026, 2:20 a.m.