Triple

T16650416
Position Surface form Disambiguated ID Type / Status
Subject 1938 Yellow River flood E404586 entity
Predicate river 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: [1938 Yellow River flood, river, Yellow River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yellow River
Context triple: [1938 Yellow River flood, river, 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37bf6cfc481909b183348c407e046 completed April 18, 2026, 12:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a50edea48190b65f4e6a9eb3ba24 completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:18 a.m.