Triple

T15158089
Position Surface form Disambiguated ID Type / Status
Subject Anshan Iron and Steel Group E362130 entity
Predicate headquartersLocation P62 FINISHED
Object Anshan E362130 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: Anshan | Statement: [Anshan Iron and Steel Group, headquartersLocation, Anshan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anshan
Context triple: [Anshan Iron and Steel Group, headquartersLocation, Anshan]
  • A. Anshan chosen
    Anshan is a major industrial city in northeastern China, historically known as one of the country’s leading steel-producing centers.
  • B. Anshan
    Anshan was an ancient city and region in southwestern Iran that served as an early center of Elamite and later Achaemenid Persian power.
  • C. Benxi
    Benxi is an industrial and mining city in eastern Liaoning Province, China, known for its steel production and nearby scenic karst landscapes.
  • D. Liaoyuan
    Liaoyuan is a prefecture-level city in northeastern China known for its coal mining history and location in the central part of Jilin Province.
  • E. Fushun
    Fushun is an industrial city in northeastern China known historically for its coal mining and heavy industry.
  • 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_69d85a0759908190b8a051d2e2a1cbe6 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0060dd71881908ecc4a4f52d438a5 completed April 15, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69febffaa4b88190aab36fdae057e6d2 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3:08 a.m.