Triple

T15265693
Position Surface form Disambiguated ID Type / Status
Subject Quzhou E364895 entity
Predicate borders P224 FINISHED
Object Lishui E367736 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: Lishui | Statement: [Quzhou, borders, Lishui]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lishui
Context triple: [Quzhou, borders, Lishui]
  • A. Lishui chosen
    Lishui is a mountainous, scenic prefecture-level city in southwestern Zhejiang Province, China, known for its rich biodiversity and eco-tourism.
  • B. Shizuishan
    Shizuishan is a major industrial city in northern China known for its coal mining and heavy industry along the Yellow River.
  • C. Jian'ou
    Jian'ou is a county-level city in northern Fujian Province, China, administered by the prefecture-level city of Nanping and known for its historical and cultural heritage.
  • D. 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.
  • E. Yueqing
    Yueqing is a county-level coastal city administered by Wenzhou in Zhejiang Province, China, known for its manufacturing industry and economic vitality.
  • 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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00851c5b88190a296b6a105d3ee30 completed April 15, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b39b6f88190ac9d6532e99fda31 completed May 9, 2026, 10:23 a.m.
Created at: April 10, 2026, 3:14 a.m.