Triple

T5599172
Position Surface form Disambiguated ID Type / Status
Subject Jilin Province E147072 entity
Predicate borderedBy P224 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: [Jilin Province, borderedBy, Heilongjiang Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heilongjiang Province
Context triple: [Jilin Province, borderedBy, 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_69c009043d648190a7af89698ccf1e3e completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020d82870819087f9591b5a1021ce completed March 22, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097c85fa481909dc6dcfccce8efa8 completed March 23, 2026, 1:30 a.m.
Created at: March 22, 2026, 3:38 p.m.