Triple
T13903345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hangzhou Metro |
E334282
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line 16
Line 16 is a suburban rapid transit line of the Hangzhou Metro system in Hangzhou, China, connecting the urban network with outlying districts.
|
E1070234
|
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: Line 16 | Statement: [Hangzhou Metro, hasLine, Line 16]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 16 Context triple: [Hangzhou Metro, hasLine, Line 16]
-
A.
Line 16
Line 16 is a rapid transit line of the Beijing Subway system serving parts of the city with modern, high-capacity metro service.
-
B.
Line 16
Line 16 is a suburban rapid transit line of the Shanghai Metro that connects central Shanghai with the southeastern outskirts, including the Lingang area.
-
C.
Line 16
Line 16 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China.
-
D.
Line 18
Line 18 is a high-speed rapid transit line of the Guangzhou Metro system in Guangzhou, China.
-
E.
Line 18
Line 18 is a planned rapid transit line of the Chongqing Metro system in Chongqing, China.
- 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: Line 16 Triple: [Hangzhou Metro, hasLine, Line 16]
Generated description
Line 16 is a suburban rapid transit line of the Hangzhou Metro system in Hangzhou, China, connecting the urban network with outlying districts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 16 Target entity description: Line 16 is a suburban rapid transit line of the Hangzhou Metro system in Hangzhou, China, connecting the urban network with outlying districts.
-
A.
Line 16
Line 16 is a rapid transit line of the Beijing Subway system serving parts of the city with modern, high-capacity metro service.
-
B.
Line 16
Line 16 is a suburban rapid transit line of the Shanghai Metro that connects central Shanghai with the southeastern outskirts, including the Lingang area.
-
C.
Line 16
Line 16 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China.
-
D.
Line 18
Line 18 is a planned rapid transit line of the Chongqing Metro system in Chongqing, China.
-
E.
Line 18
Line 18 is a high-speed rapid transit line of the Guangzhou Metro system in Guangzhou, China.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25db1e308190aaed6a21e443cc44 |
completed | April 14, 2026, 11:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce7638a88190aae1b59c00ee27ce |
completed | May 3, 2026, 10:38 p.m. |
| NEDg | Description generation | batch_69f9fd56da288190b2bd33bc496c3fb9 |
completed | May 5, 2026, 2:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fb039fdb1c8190ad5286d1cfe80a29 |
completed | May 6, 2026, 9:02 a.m. |
Created at: April 9, 2026, 10:16 p.m.