Triple

T16919429
Position Surface form Disambiguated ID Type / Status
Subject Xiong’an New Area E410405 entity
Predicate locatedNear P294 FINISHED
Object Baoding E143804 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: Baoding | Statement: [Xiong’an New Area, locatedNear, Baoding]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baoding
Context triple: [Xiong’an New Area, locatedNear, Baoding]
  • A. Baoding chosen
    Baoding is a historic prefecture-level city in central Hebei Province, China, known as a regional transportation hub and former military and administrative center.
  • B. Changzhi
    Changzhi is a major city in southeastern Shanxi Province, China, known as a regional industrial and transportation hub with a long historical and cultural heritage.
  • 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. Chengde
    Chengde is a historic city in northeastern China best known for its Qing dynasty Mountain Resort, a vast imperial summer retreat and UNESCO World Heritage Site.
  • E. Langfang
    Langfang is a prefecture-level city in northern China situated between Beijing and Tianjin, known for its strategic location and growing industrial and service sectors.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cded2f8481909a20cc08b47e922e completed April 18, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7c2c9cc8190b6d59d0a8edd078d completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:30 a.m.