Triple

T14753756
Position Surface form Disambiguated ID Type / Status
Subject 海河 E346677 entity
Predicate relatedCity P24465 FINISHED
Object 石家庄 E79577 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: 石家庄 | Statement: [海河, relatedCity, 石家庄]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 石家庄
Context triple: [海河, relatedCity, 石家庄]
  • A. 邯郸市
    邯郸市 is a historically significant prefecture-level city in southern Hebei Province, China, known as an ancient capital and important industrial and transportation hub in the North China Plain.
  • B. Shijiazhuang chosen
    Shijiazhuang is the capital and largest city of Hebei Province in northern China, known as a major industrial and transportation hub.
  • C. Cangzhou
    Cangzhou is a prefecture-level city in eastern Hebei Province, China, known for its location near the Bohai Sea and its traditional martial arts heritage.
  • D. Baoding
    Baoding is a historic prefecture-level city in central Hebei Province, China, known as a regional transportation hub and former military and administrative center.
  • E. Hengshui
    Hengshui is a prefecture-level city in southeastern Hebei Province, China, known for its traditional culture, agriculture, and growing industrial base.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7d59df08190a86da5048358bd6e completed April 14, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb9c725881908004368772fa528d completed May 8, 2026, 3:05 p.m.
Created at: April 10, 2026, 1:30 a.m.