Triple

T4283344
Position Surface form Disambiguated ID Type / Status
Subject Kaiyuan Temple E97206 entity
Predicate locatedIn P40 FINISHED
Object Quanzhou E97206 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: Quanzhou | Statement: [Kaiyuan Temple, locatedIn, Quanzhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quanzhou
Context triple: [Kaiyuan Temple, locatedIn, Quanzhou]
  • A. Quanzhou chosen
    Quanzhou is a historic coastal city in southeastern China that flourished as one of the world’s busiest maritime trade hubs, especially during the Song and Yuan dynasties.
  • B. Zhangzhou
    Zhangzhou is a historic coastal city in southeastern China known for its agriculture, traditional Minnan culture, and proximity to Xiamen in Fujian Province.
  • C. Xiamen
    Xiamen is a major coastal city in southeastern China known for its port, tourism, and historic role as one of the country’s earliest Special Economic Zones.
  • D. Fuzhou
    Fuzhou is the capital and largest city of China’s Fujian Province, known as a major coastal and river port with a long history of maritime trade and cultural exchange.
  • E. Ningde
    Ningde is a coastal prefecture-level city in northeastern Fujian Province, China, known for its mountainous landscapes, marine economy, and as the headquarters of battery giant CATL.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3503a84548190989a96d1a30d6ef7 completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d069a3c08190abbbf4f163c31054 completed March 14, 2026, 9:17 p.m.
Created at: March 12, 2026, 11:07 p.m.