Triple

T19720989
Position Surface form Disambiguated ID Type / Status
Subject Fengze District E473606 entity
Predicate locatedNear P294 FINISHED
Object Licheng District NE NERFINISHED

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: Licheng District | Statement: [Fengze District, locatedNear, Licheng District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Licheng District
Context triple: [Fengze District, locatedNear, Licheng District]
  • A. Licheng District chosen
    Licheng District is a central urban district of Quanzhou in Fujian Province, China, known for its historic architecture and cultural heritage.
  • B. Lucheng District
    Lucheng District is the central urban district and administrative, commercial, and cultural core of Wenzhou in Zhejiang Province, China.
  • C. Lucheng District
    Lucheng District is the central urban district and administrative seat of Changzhi, a prefecture-level city in Shanxi Province, China.
  • D. Wucheng District
    Wucheng District is the central urban district and administrative seat of the prefecture-level city of Jinhua in Zhejiang Province, China.
  • E. Hecheng District
    Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e516dd048190a0b6c93ea3e71f58 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e649f483c481908c6b3114bf9c5934 completed April 20, 2026, 3:44 p.m.
Created at: April 10, 2026, 1:46 p.m.