Triple

T7384773
Position Surface form Disambiguated ID Type / Status
Subject Jiangdongmen area E170352 entity
Predicate hasTransportConnection P845 FINISHED
Object Nanjing Metro E170351 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 Metro | Statement: [Jiangdongmen area, hasTransportConnection, Nanjing Metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanjing Metro
Context triple: [Jiangdongmen area, hasTransportConnection, Nanjing Metro]
  • A. Nanjing Metro chosen
    Nanjing Metro is the rapid transit system serving the city of Nanjing, China, comprising multiple urban and suburban lines that form a major part of the city's public transportation network.
  • B. Changzhou Metro
    Changzhou Metro is the urban rapid transit system serving the city of Changzhou in Jiangsu Province, China.
  • C. Hangzhou Metro
    Hangzhou Metro is the rapid transit system serving the city of Hangzhou, China, providing urban and suburban rail transportation across the metropolitan area.
  • D. Hefei Metro
    Hefei Metro is the rapid transit system serving Hefei, the capital city of China’s Anhui Province, providing urban rail transportation across the metropolitan area.
  • E. Nanchang Metro
    Nanchang Metro is the rapid transit system serving the city of Nanchang in Jiangxi Province, China.
  • 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_69c68a5d0ed08190b6d361e68f813330 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1efe1308190b96eefbff56140be completed March 27, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802e23714819094a1b31c82a27fee completed March 28, 2026, 4:33 p.m.
Created at: March 27, 2026, 3:08 p.m.