Triple

T7413528
Position Surface form Disambiguated ID Type / Status
Subject Heihe E171068 entity
Predicate belongsTo P35 FINISHED
Object Heilongjiang Province E114388 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: Heilongjiang Province | Statement: [Heihe, belongsTo, Heilongjiang Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heilongjiang Province
Context triple: [Heihe, belongsTo, Heilongjiang Province]
  • A. Heilongjiang chosen
    Heilongjiang is a northeastern Chinese province known for its cold climate, heavy industry, and border with Russia.
  • B. Jilin Province
    Jilin Province is a northeastern Chinese province in the historical region of Manchuria, known for its cold climate, heavy industry, and significant Korean ethnic minority.
  • C. Liaoning
    Liaoning is a northeastern coastal province of China known for its heavy industry, port cities, and role as a gateway to the Korean Peninsula.
  • D. Hebei
    Hebei is a northern Chinese province surrounding Beijing and Tianjin, historically significant as a major political, military, and industrial region.
  • E. Daqing
    Daqing is a major industrial city in northeastern China best known for its large oil fields and role as a center of the country’s petroleum industry.
  • 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_69c68a618bdc81908d8018edadecd1a4 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f2c336308190932c14cec5eec25f completed March 27, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c4dc1c08190876eb0e70f387b77 completed March 28, 2026, 8:38 p.m.
Created at: March 27, 2026, 3:11 p.m.