Triple

T2831931
Position Surface form Disambiguated ID Type / Status
Subject Tungusic languages E62256 entity
Predicate geographicDistribution P2178 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: [Tungusic languages, geographicDistribution, Heilongjiang Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heilongjiang Province
Context triple: [Tungusic languages, geographicDistribution, 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. Hubei Province
    Hubei Province is a landlocked region in central China known for its capital city Wuhan, major role in industry and transportation, and significant historical and cultural heritage.
  • 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_69ab4c3c39188190955b9c49d98463d8 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdebe95188190bf65fb4cd88e2ec5 completed March 7, 2026, 8:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0312dd4848190b30f6fcc11c2c954 completed March 10, 2026, 2:56 p.m.
Created at: March 6, 2026, 10:01 p.m.