Triple

T8532598
Position Surface form Disambiguated ID Type / Status
Subject Guangzhou Metro Line 7 E201990 entity
Predicate hasStation P35 FINISHED
Object Dashi
Dashi is a metro station on Guangzhou's Line 7 serving the Panyu District area of Guangzhou, China.
 E740231 NE FINISHED

How this triple was built (4 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: Dashi | Statement: [Guangzhou Metro Line 7, hasStation, Dashi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dashi
Context triple: [Guangzhou Metro Line 7, hasStation, Dashi]
  • A. Nori
    Nori is a given name, often used as a short or affectionate form of longer names such as Nora.
  • B. Oshiage
    Oshiage is a district in Sumida, Tokyo, best known as the location of the Tokyo Skytree and its surrounding commercial complex.
  • C. Ma Kai
    Ma Kai is a Chinese politician who served as a Vice Premier of the State Council and played a key role in the country’s economic and financial policymaking.
  • D. Masago
    Masago is the wife of the murdered samurai in Ryūnosuke Akutagawa’s short story "In a Grove," whose conflicting testimony is central to the tale’s exploration of truth and perspective.
  • E. Unami
    Unami is a dialect of the Lenape (Delaware) language historically spoken by the Lenape people in parts of the mid-Atlantic region of North America.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dashi
Triple: [Guangzhou Metro Line 7, hasStation, Dashi]
Generated description
Dashi is a metro station on Guangzhou's Line 7 serving the Panyu District area of Guangzhou, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dashi
Target entity description: Dashi is a metro station on Guangzhou's Line 7 serving the Panyu District area of Guangzhou, China.
  • A. Nori
    Nori is a given name, often used as a short or affectionate form of longer names such as Nora.
  • B. Oshiage
    Oshiage is a district in Sumida, Tokyo, best known as the location of the Tokyo Skytree and its surrounding commercial complex.
  • C. Ma Kai
    Ma Kai is a Chinese politician who served as a Vice Premier of the State Council and played a key role in the country’s economic and financial policymaking.
  • D. Masago
    Masago is the wife of the murdered samurai in Ryūnosuke Akutagawa’s short story "In a Grove," whose conflicting testimony is central to the tale’s exploration of truth and perspective.
  • E. Unami
    Unami is a dialect of the Lenape (Delaware) language historically spoken by the Lenape people in parts of the mid-Atlantic region of North America.
  • F. None of above. chosen

Provenance (5 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_69ce6d70f81881908ac784608ad7a2aa completed April 2, 2026, 1:21 p.m.
NEDg Description generation batch_69ce6e69213c8190add7eb9cc74b1a33 completed April 2, 2026, 1:26 p.m.
NED2 Entity disambiguation (via description) batch_69ce6f28ae6481909a8a13613f3eb5e0 completed April 2, 2026, 1:29 p.m.
Created at: March 30, 2026, 6:17 p.m.