Triple
T22441808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chengdu Metro Line 1 |
E554769
|
entity |
| Predicate | servesStation |
P839
|
FINISHED |
| Object |
Sichuan Gymnasium station
Sichuan Gymnasium station is a metro station in Chengdu, China, providing access to the Sichuan Gymnasium and surrounding commercial and residential areas.
|
E1539581
|
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: Sichuan Gymnasium station | Statement: [Chengdu Metro Line 1, servesStation, Sichuan Gymnasium station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sichuan Gymnasium station Context triple: [Chengdu Metro Line 1, servesStation, Sichuan Gymnasium station]
-
A.
Sichuan Road North station
Sichuan Road North station is an underground metro stop in Shanghai, China, serving passengers on the city's Line 10.
-
B.
Xicun Station
Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
-
C.
Shuichan Road station
Shuichan Road station is a metro station in Shanghai, China, serving passengers in the Baoshan District as part of the city's urban rail transit network.
-
D.
Shuicheng Road Station
Shuicheng Road Station is a Shanghai Metro station serving the Changning District in Shanghai, China.
-
E.
Zhongyi station
Zhongyi station is a metro station on the Taipei Metro system in New Taipei City, Taiwan.
- 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: Sichuan Gymnasium station Triple: [Chengdu Metro Line 1, servesStation, Sichuan Gymnasium station]
Generated description
Sichuan Gymnasium station is a metro station in Chengdu, China, providing access to the Sichuan Gymnasium and surrounding commercial and residential areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sichuan Gymnasium station Target entity description: Sichuan Gymnasium station is a metro station in Chengdu, China, providing access to the Sichuan Gymnasium and surrounding commercial and residential areas.
-
A.
Sichuan Road North station
Sichuan Road North station is an underground metro stop in Shanghai, China, serving passengers on the city's Line 10.
-
B.
Xicun Station
Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
-
C.
Shuichan Road station
Shuichan Road station is a metro station in Shanghai, China, serving passengers in the Baoshan District as part of the city's urban rail transit network.
-
D.
Shuicheng Road Station
Shuicheng Road Station is a Shanghai Metro station serving the Changning District in Shanghai, China.
-
E.
Zhongyi station
Zhongyi station is a metro station on the Taipei Metro system in New Taipei City, Taiwan.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae2f7608190b1c1e8bd12ca2162 |
completed | April 29, 2026, 1:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b124f0c1c81909c77fcb46e3af1e2 |
completed | May 18, 2026, 1:21 p.m. |
| NEDg | Description generation | batch_6a0b14a059e4819095a3d467c469e783 |
completed | May 18, 2026, 1:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b15696e588190a2c76b0a4af285a4 |
completed | May 18, 2026, 1:34 p.m. |
Created at: April 16, 2026, 8:47 p.m.