Triple

T13210548
Position Surface form Disambiguated ID Type / Status
Subject Shitai Expressway E314477 entity
Predicate connectsRegion P845 FINISHED
Object Hebei E11863 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: Hebei | Statement: [Shitai Expressway, connectsRegion, Hebei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hebei
Context triple: [Shitai Expressway, connectsRegion, Hebei]
  • A. Hebei chosen
    Hebei is a northern Chinese province surrounding Beijing and Tianjin, historically significant as a major political, military, and industrial region.
  • B. 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.
  • C. 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.
  • D. Shandong
    Shandong is a coastal province in eastern China that has historically been a significant political, military, and cultural center, notably during various conflicts in modern Chinese history.
  • E. Kansu
    Kansu is a Turkish surname most notably associated with Şevket Aziz Kansu, a prominent Turkish academic and anthropologist.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c9e072c8190b66e2c2430628ed0 completed April 10, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7305a8c108190aff4e4797370f3d3 completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:17 p.m.