Triple

T16179374
Position Surface form Disambiguated ID Type / Status
Subject Nanjing Automobile E392646 entity
Predicate headquartersLocation P62 FINISHED
Object Nanjing E29741 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: Nanjing | Statement: [Nanjing Automobile, headquartersLocation, Nanjing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanjing
Context triple: [Nanjing Automobile, headquartersLocation, Nanjing]
  • A. Nanjing chosen
    Nanjing is a major city in eastern China, historically significant as a former national capital and cultural center, and now an important political, economic, and educational hub on the Yangtze River.
  • B. Zhenjiang
    Zhenjiang is a historic port city in eastern China known for its strategic location on the Yangtze River and its rich cultural and culinary heritage.
  • C. Wuxi
    Wuxi is a major industrial and cultural city in eastern China, located near Lake Tai and known for its manufacturing, canals, and historic gardens.
  • D. Changzhou
    Changzhou is a major industrial and commercial city in Jiangsu Province, eastern China, known for its manufacturing base and location along the Yangtze River.
  • E. Yangzhou
    Yangzhou is a historic city in eastern China renowned for its canals, gardens, and role as a major cultural and commercial center along the Grand Canal.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e2205b88b481908ecdd8d663dc668b completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a000787d3fc8190a32d53a177fedb6d completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 5:02 a.m.