Triple

T11271053
Position Surface form Disambiguated ID Type / Status
Subject Lawrence, Kansas E266811 entity
Predicate hasNickname P39 FINISHED
Object River City E184012 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: River City | Statement: [Lawrence, Kansas, hasNickname, River City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: River City
Context triple: [Lawrence, Kansas, hasNickname, River City]
  • A. River City
    River City is a popular nickname for Richmond, Virginia, highlighting the city's location along the James River and its historic riverfront character.
  • B. River City chosen
    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.
  • C. River City
    River City is a popular nickname for Sacramento, California, highlighting the city’s close connection to the nearby American and Sacramento Rivers.
  • D. 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.
  • E. Ice City
    Ice City is the popular nickname for Harbin, a major northeastern Chinese city renowned for its frigid winters and spectacular ice and snow sculptures.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9506204819089dc0827483bd948 completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f4229c7081909da6b22ee6bf4905 completed April 19, 2026, 3:26 p.m.
Created at: April 8, 2026, 9:31 p.m.