Triple

T12512632
Position Surface form Disambiguated ID Type / Status
Subject Chungking E299116 entity
Predicate hasNickname P39 FINISHED
Object Fog City E192026 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: Fog City | Statement: [Chungking, hasNickname, Fog City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fog City
Context triple: [Chungking, hasNickname, Fog City]
  • A. Fog City chosen
    Fog City is a popular nickname for Chongqing, a major southwestern Chinese metropolis famous for its humid, mist-covered climate and dense urban landscape.
  • B. Fog City
    Fog City is a popular nickname for San Francisco, highlighting the city's famously frequent fog.
  • C. River City
    River City is a popular nickname for Wuhan, a major central Chinese metropolis known for its location at the confluence of the Yangtze and Han rivers.
  • D. River City
    River City is a common nickname and place name in the United States, often referring to cities situated along major rivers and popularized in American culture and media.
  • E. River City
    River City is a popular nickname for Sacramento, California, highlighting the city’s close connection to the nearby American and Sacramento Rivers.
  • 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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541d6e508190a4992f328e077467 completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bbba5fc819082a4171a5a77183a completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:57 p.m.