Triple

T11588232
Position Surface form Disambiguated ID Type / Status
Subject HMS Aurora E274807 entity
Predicate laterName P65 FINISHED
Object Huang He 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: Huang He | Statement: [HMS Aurora, laterName, Huang He]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Huang He
Context triple: [HMS Aurora, laterName, Huang He]
  • A. 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.
  • B. Yellow River
    The Yellow River is a tributary stream that feeds into Lough Allen, a lake in the River Shannon system in Ireland.
  • C. 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.
  • 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. Yangtze River
    The Yangtze River is the longest river in Asia and a crucial waterway in China, supporting major cities, transportation, agriculture, and hydroelectric power.
  • 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_69d6aae6b14c81908dc5a74bad7591f9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d89463360c8190b91228c46bfe2e5f completed April 10, 2026, 6:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69e71451f1388190b72d7b755d198999 completed April 21, 2026, 6:08 a.m.
Created at: April 8, 2026, 9:38 p.m.