Triple

T8532601
Position Surface form Disambiguated ID Type / Status
Subject Guangzhou Metro Line 7 E201990 entity
Predicate hasStation P35 FINISHED
Object Meidi Dadao E740227 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: Meidi Dadao | Statement: [Guangzhou Metro Line 7, hasStation, Meidi Dadao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meidi Dadao
Context triple: [Guangzhou Metro Line 7, hasStation, Meidi Dadao]
  • A. Meidi Dadao chosen
    Meidi Dadao is a metro station in Guangzhou, China, serving as a terminus on Guangzhou Metro Line 7.
  • B. Zhujiajiao
    Zhujiajiao is an ancient water town on the outskirts of Shanghai, famed for its historic canals, stone bridges, and traditional architecture.
  • C. Xiadu
    Xiadu was an ancient Chinese city that served as a major political and cultural center of the Warring States–period Yan kingdom.
  • D. Da Yuan
    Da Yuan is the official Chinese name for the Yuan dynasty, the Mongol-ruled imperial dynasty that governed China from the late 13th to the mid-14th century.
  • E. Xiaomeisha
    Xiaomeisha is a popular coastal resort area in Shenzhen, China, known for its sandy beaches, seaside recreation, and tourist attractions.
  • 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_69ca832355b08190b8b6a4ab4a4a3554 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe678fe448190a50c6b0d149b081f completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce890333d08190b510d970e6d6fee5 completed April 2, 2026, 3:19 p.m.
Created at: March 30, 2026, 6:17 p.m.