Triple
T17796067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shenzhen Metro Line 3 |
E444294
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Dafen station
Dafen station is a metro station in Shenzhen, China, serving passengers on the city's Line 3.
|
E1368114
|
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: Dafen station | Statement: [Shenzhen Metro Line 3, hasStation, Dafen station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dafen station Context triple: [Shenzhen Metro Line 3, hasStation, Dafen station]
-
A.
Dapinglin station
Dapinglin station is a metro station on the Taipei Metro system in New Taipei City, Taiwan.
-
B.
Yitian station
Yitian station is a metro station in Shenzhen, China, serving as the southern terminus of Shenzhen Metro Line 3.
-
C.
Wanshengwei Station
Wanshengwei Station is a metro station in Guangzhou, China, serving as a transport hub within the Guangzhou Metro network.
-
D.
Weiwuying Station
Weiwuying Station is an underground metro station in Kaohsiung, Taiwan, serving the Weiwuying area and providing access to the nearby National Kaohsiung Center for the Arts.
-
E.
Qibao Station
Qibao Station is a Shanghai Metro station serving the historic Qibao area in Minhang District, known for providing convenient transit access to this popular suburban neighborhood.
- 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: Dafen station Triple: [Shenzhen Metro Line 3, hasStation, Dafen station]
Generated description
Dafen station is a metro station in Shenzhen, China, serving passengers on the city's Line 3.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dafen station Target entity description: Dafen station is a metro station in Shenzhen, China, serving passengers on the city's Line 3.
-
A.
Dapinglin station
Dapinglin station is a metro station on the Taipei Metro system in New Taipei City, Taiwan.
-
B.
Yitian station
Yitian station is a metro station in Shenzhen, China, serving as the southern terminus of Shenzhen Metro Line 3.
-
C.
Wanshengwei Station
Wanshengwei Station is a metro station in Guangzhou, China, serving as a transport hub within the Guangzhou Metro network.
-
D.
Weiwuying Station
Weiwuying Station is an underground metro station in Kaohsiung, Taiwan, serving the Weiwuying area and providing access to the nearby National Kaohsiung Center for the Arts.
-
E.
Qibao Station
Qibao Station is a Shanghai Metro station serving the historic Qibao area in Minhang District, known for providing convenient transit access to this popular suburban neighborhood.
- 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487fafc2c8190b28e791267c47e3c |
completed | April 19, 2026, 7:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a070e5577d08190875d8a408ca80e51 |
completed | May 15, 2026, 12:15 p.m. |
| NEDg | Description generation | batch_6a070f388fb88190ba66f6b61db40d92 |
completed | May 15, 2026, 12:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a071018f61881908ace460b83dac186 |
completed | May 15, 2026, 12:22 p.m. |
Created at: April 10, 2026, 10:13 a.m.