Triple

T8186194
Position Surface form Disambiguated ID Type / Status
Subject Jiaoling Hakka E191189 entity
Predicate spokenIn P2266 FINISHED
Object Meizhou City E708131 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: Meizhou City | Statement: [Jiaoling Hakka, spokenIn, Meizhou City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meizhou City
Context triple: [Jiaoling Hakka, spokenIn, Meizhou City]
  • A. Meizhou chosen
    Meizhou is a city in eastern Guangdong, China, known as a cultural and historical center of the Hakka people.
  • B. Mianyang
    Mianyang is a major city in southwestern China known as an important industrial and technological center within Sichuan Province.
  • C. Yibin
    Yibin is a historic prefecture-level city in southwestern China known as the "First City on the Yangtze River," where the Jinsha and Min rivers converge to form the Yangtze.
  • D. Xichang
    Xichang is a city in Sichuan Province, China, known as a major hub for the country’s space launch activities and related aerospace industry.
  • E. Nanchong
    Nanchong is a major city in northeastern Sichuan Province, China, known as a regional transportation and economic hub with a long historical and cultural heritage.
  • 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_69ca82c5b6948190a583c096fb0a6c71 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4c52407c8190bd366fce6d4e02cd completed March 31, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd94bbdc288190aee5187e95ca7a8d completed April 1, 2026, 9:57 p.m.
Created at: March 30, 2026, 5:41 p.m.