Triple
T9547228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Metro Line 3 |
E230322
|
entity |
| Predicate | depot |
P14646
|
FINISHED |
| Object |
Shilong Road depot
Shilong Road depot is a maintenance and storage facility serving trains on Shanghai Metro Line 3.
|
E807557
|
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: Shilong Road depot | Statement: [Shanghai Metro Line 3, depot, Shilong Road depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shilong Road depot Context triple: [Shanghai Metro Line 3, depot, Shilong Road depot]
-
A.
Meilong Depot
Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
-
B.
Dahua Road depot
Dahua Road depot is a maintenance and storage facility serving Shanghai Metro’s Line 7.
-
C.
Wanshengwei Depot
Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
-
D.
Tuqiao Depot
Tuqiao Depot is a maintenance and storage facility serving trains on Beijing’s Batong Line of the subway system.
-
E.
Daliao Depot
Daliao Depot is a maintenance and storage facility serving trains on the Kaohsiung Mass Rapid Transit system in Kaohsiung, 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: Shilong Road depot Triple: [Shanghai Metro Line 3, depot, Shilong Road depot]
Generated description
Shilong Road depot is a maintenance and storage facility serving trains on Shanghai Metro Line 3.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shilong Road depot Target entity description: Shilong Road depot is a maintenance and storage facility serving trains on Shanghai Metro Line 3.
-
A.
Meilong Depot
Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
-
B.
Dahua Road depot
Dahua Road depot is a maintenance and storage facility serving Shanghai Metro’s Line 7.
-
C.
Wanshengwei Depot
Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
-
D.
Tuqiao Depot
Tuqiao Depot is a maintenance and storage facility serving trains on Beijing’s Batong Line of the subway system.
-
E.
Daliao Depot
Daliao Depot is a maintenance and storage facility serving trains on the Kaohsiung Mass Rapid Transit system in Kaohsiung, 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_69ca847c70b8819088a0a0bad64a50d6 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9904732c8190ab60ecc47c995cbe |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1527c0914819087ffa9d201afdd35 |
completed | April 4, 2026, 6:03 p.m. |
| NEDg | Description generation | batch_69d153d59844819086a0f50e6a7624b2 |
completed | April 4, 2026, 6:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1546a503c81908edc9588adabc172 |
completed | April 4, 2026, 6:11 p.m. |
Created at: March 30, 2026, 8:02 p.m.