Triple

T8573092
Position Surface form Disambiguated ID Type / Status
Subject Bayannur E202975 entity
Predicate locatedOnRiver P165 FINISHED
Object Yellow River E16374 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: Yellow River | Statement: [Bayannur, locatedOnRiver, Yellow River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yellow River
Context triple: [Bayannur, locatedOnRiver, Yellow River]
  • A. Yellow River chosen
    The Yellow River is the second-longest river in China, historically known as the cradle of Chinese civilization and notorious for its devastating floods and heavy silt load.
  • B. Yellow River
    The Yellow River is a river in the U.S. state of Florida that flows through the western Panhandle before emptying into Escambia Bay near the Gulf of Mexico.
  • C. Yellow River
    The Yellow River is a tributary stream that feeds into Lough Allen, a lake in the River Shannon system in Ireland.
  • D. Hwang River
    The Hwang River is a river in South Korea that feeds into the Nakdong River, contributing to one of the country’s major watershed systems.
  • E. Chang River
    The Chang River is a significant waterway flowing through Jingdezhen, a city in Jiangxi Province renowned for its porcelain production.
  • 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_69ca8328ebe481909a8c038fa79959b4 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbea458c1081908e79bee2cbf97207 completed March 31, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69d09b22da4c81909aacc9c4a6af379c completed April 4, 2026, 5:01 a.m.
Created at: March 30, 2026, 6:21 p.m.