Triple

T3826790
Position Surface form Disambiguated ID Type / Status
Subject Mazu E88708 entity
Predicate placeOfOrigin P3743 FINISHED
Object Putian E288003 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: Putian | Statement: [Mazu, placeOfOrigin, Putian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Putian
Context triple: [Mazu, placeOfOrigin, Putian]
  • A. Putian chosen
    Putian is a coastal prefecture-level city in southeastern China known for its manufacturing industries, especially footwear, and its historical and cultural heritage within Fujian province.
  • B. Longyan
    Longyan is a prefecture-level city in western Fujian Province, China, known for its Hakka culture, mountainous landscapes, and historic tulou earthen dwellings.
  • C. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • D. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • E. Liyang
    Liyang is a county-level city in Jiangsu Province, China, known for its scenic attractions such as Tianmu Lake and its administration under the prefecture-level city of Changzhou.
  • 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_69aed9538cf881909d9ce8ca4ac7c18c completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeeb64c72c8190b5f3d376aa4ee933 completed March 9, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51222e5b08190aa4ac79722219798 completed March 14, 2026, 7:45 a.m.
Created at: March 9, 2026, 3:17 p.m.