Triple

T3956881
Position Surface form Disambiguated ID Type / Status
Subject Amagasaki E85802 entity
Predicate hasSisterCity P919 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: [Amagasaki, hasSisterCity, Anshan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anshan
Context triple: [Amagasaki, hasSisterCity, Anshan]
  • A. Anshan
    Anshan was an ancient city and region in southwestern Iran that served as an early center of Elamite and later Achaemenid Persian power.
  • B. Anshan chosen
    Anshan is a major industrial city in northeastern China, historically known as one of the country’s leading steel-producing centers.
  • 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. Fushun
    Fushun is an industrial city in northeastern China known historically for its coal mining and heavy industry.
  • E. Jinzhou
    Jinzhou is a prefecture-level port city in southwestern Liaoning Province, northeastern China, known for its industrial base and coastal location on the Bohai Sea.
  • 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_69aed93a96908190bcbdbfa718f155bd completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef95bbb9c8190bd64c5b7ea2f341a completed March 9, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55619cb548190ac2553f23de9bfed completed March 14, 2026, 12:35 p.m.
Created at: March 9, 2026, 3:31 p.m.