Triple

T16138399
Position Surface form Disambiguated ID Type / Status
Subject Caizhou E391588 entity
Predicate region P40 FINISHED
Object Central Plains E314064 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: Central Plains | Statement: [Caizhou, region, Central Plains]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Central Plains
Context triple: [Caizhou, region, Central Plains]
  • A. Central Plains region chosen
    The Central Plains region is a key economic and cultural heartland of China, centered around the middle and lower reaches of the Yellow River and encompassing major inland cities and agricultural areas.
  • B. Great Plains
    The Great Plains is a vast, mostly flat grassland region in central North America known for its prairies, agriculture, and continental climate.
  • C. Southern Great Plain
    The Southern Great Plain is a large, predominantly flat agricultural region in southeastern Hungary known for its fertile lands and extensive farming.
  • D. Northern Great Plain
    The Northern Great Plain is a large, predominantly flat agricultural and economic region in eastern Hungary that includes major cities such as Debrecen.
  • E. Southeastern Plains
    The Southeastern Plains is a broad, low-lying ecoregion of the southeastern United States characterized by gently rolling terrain, extensive forests, and mixed agricultural and rural landscapes.
  • 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_69d87f1bb0988190b490d273dbf3fd03 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21a06e0988190b5cd62d422d058a2 completed April 17, 2026, 11:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69fffef0f51c8190bc039150af8ebf98 completed May 10, 2026, 3:43 a.m.
Created at: April 10, 2026, 5:01 a.m.