Triple

T17782734
Position Surface form Disambiguated ID Type / Status
Subject Matsumoto, Nagano, Japan E443937 entity
Predicate twinnedWith P1072 FINISHED
Object Langfang 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: Langfang | Statement: [Matsumoto, Nagano, Japan, twinnedWith, Langfang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Langfang
Context triple: [Matsumoto, Nagano, Japan, twinnedWith, Langfang]
  • A. Langfang chosen
    Langfang is a prefecture-level city in northern China situated between Beijing and Tianjin, known for its strategic location and growing industrial and service sectors.
  • B. Cangzhou
    Cangzhou is a prefecture-level city in eastern Hebei Province, China, known for its location near the Bohai Sea and its traditional martial arts heritage.
  • C. Baoding
    Baoding is a historic prefecture-level city in central Hebei Province, China, known as a regional transportation hub and former military and administrative center.
  • D. Zhuozhou City
    Zhuozhou City is a county-level city in Hebei Province, China, located southwest of Beijing and known for its role as a regional transportation and agricultural hub.
  • E. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • 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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4872260b881908e77096500451816 completed April 19, 2026, 7:41 a.m.
Created at: April 10, 2026, 10:12 a.m.