Triple

T17943651
Position Surface form Disambiguated ID Type / Status
Subject Laixi E448645 entity
Predicate hasProvinceCapital P3433 FINISHED
Object Jinan NE NERFINISHED

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: Jinan | Statement: [Laixi, hasProvinceCapital, Jinan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jinan
Context triple: [Laixi, hasProvinceCapital, Jinan]
  • A. Jinan chosen
    Jinan is the capital city of Shandong Province in eastern China, known for its numerous natural springs and rich historical and cultural heritage.
  • B. Jining
    Jining is a city in Shandong Province, China, historically significant as a transport and commercial hub along the Grand Canal.
  • C. Yantai
    Yantai is a coastal city in Shandong Province, China, known for its port, wine production, and scenic beaches along the Bohai Sea.
  • D. Linyi
    Linyi is a major prefecture-level city in southeastern Shandong Province, China, known for its large population, historical significance, and role as a regional commercial and logistics hub.
  • E. Taian
    Taian is a prefecture-level city in eastern China's Shandong province, best known as the gateway to the sacred Mount Tai.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f8cca8819099836916c56b7c95 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4ad97611c8190a861467ae51f6c48 completed April 19, 2026, 10:25 a.m.
Created at: April 10, 2026, 10:21 a.m.