Triple
T9926487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guangzhou Metro Line 2 |
E187935
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object |
Nanpu station
Nanpu station is a metro station in Guangzhou, China, serving passengers on the city’s Line 2 rapid transit route.
|
E840229
|
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: Nanpu station | Statement: [Guangzhou Metro Line 2, connects, Nanpu station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nanpu station Context triple: [Guangzhou Metro Line 2, connects, Nanpu station]
-
A.
Chunxi Road Station
Chunxi Road Station is a major metro station in Chengdu, China, providing access to the popular commercial and shopping district around Chunxi Road.
-
B.
Hongqiao Road Station
Hongqiao Road Station is a major Shanghai Metro interchange station serving multiple lines in the western part of the city.
-
C.
Xujiahui Station
Xujiahui Station is a major Shanghai Metro interchange and commercial hub serving the busy Xujiahui area in Shanghai, China.
-
D.
Xinzhuang Station
Xinzhuang Station is a major Shanghai Metro interchange station in Minhang District, serving as a key southern transport hub in the city’s network.
-
E.
Wudaokou station
Wudaokou station is a busy Beijing Subway stop in the Haidian District, known for serving a major university and tech hub area popular with students and young professionals.
- 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: Nanpu station Triple: [Guangzhou Metro Line 2, connects, Nanpu station]
Generated description
Nanpu station is a metro station in Guangzhou, China, serving passengers on the city’s Line 2 rapid transit route.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nanpu station Target entity description: Nanpu station is a metro station in Guangzhou, China, serving passengers on the city’s Line 2 rapid transit route.
-
A.
Chunxi Road Station
Chunxi Road Station is a major metro station in Chengdu, China, providing access to the popular commercial and shopping district around Chunxi Road.
-
B.
Hongqiao Road Station
Hongqiao Road Station is a major Shanghai Metro interchange station serving multiple lines in the western part of the city.
-
C.
Xujiahui Station
Xujiahui Station is a major Shanghai Metro interchange and commercial hub serving the busy Xujiahui area in Shanghai, China.
-
D.
Xinzhuang Station
Xinzhuang Station is a major Shanghai Metro interchange station in Minhang District, serving as a key southern transport hub in the city’s network.
-
E.
Wudaokou station
Wudaokou station is a busy Beijing Subway stop in the Haidian District, known for serving a major university and tech hub area popular with students and young professionals.
- 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_69ca82b22a688190b52c75bd48429c10 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb599e32c8190ac676fa89c131bb6 |
completed | April 2, 2026, 12:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b5c126c081909a072034fde64a04 |
completed | April 5, 2026, 7:19 p.m. |
| NEDg | Description generation | batch_69d2b741cad481909f04e2f8da68753c |
completed | April 5, 2026, 7:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d2b805afa08190a43745d764a75050 |
completed | April 5, 2026, 7:29 p.m. |
Created at: March 30, 2026, 8:43 p.m.