Triple

T8903320
Position Surface form Disambiguated ID Type / Status
Subject Mount Emei E211984 entity
Predicate nearCity P350 FINISHED
Object Emeishan City E567789 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: Emeishan City | Statement: [Mount Emei, nearCity, Emeishan City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emeishan City
Context triple: [Mount Emei, nearCity, Emeishan City]
  • A. Enshi City
    Enshi City is a county-level city in southwestern Hubei Province, China, known for its mountainous karst landscapes and role as a cultural center for the Tujia and Miao ethnic groups.
  • B. Meishan chosen
    Meishan is a county-level city in Sichuan Province, China, known as the hometown of the famous Song dynasty poet Su Shi and for its rich cultural heritage and agricultural surroundings.
  • C. Zunhua City
    Zunhua City is a county-level city in northeastern Hebei Province, China, known for its historical sites and administrative affiliation with the prefecture-level city of Tangshan.
  • D. Shizuishan
    Shizuishan is a major industrial city in northern China known for its coal mining and heavy industry along the Yellow River.
  • E. Xianning
    Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
  • 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_69ca839255248190b43984294abd92ae completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc64c091d08190b59e54eb4a184e41 completed April 1, 2026, 12:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffd78f35881909c15249b58a1ce03 completed April 3, 2026, 5:48 p.m.
Created at: March 30, 2026, 6:55 p.m.