Triple
T2383248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Changning District |
E46358
|
entity |
| Predicate | hasMetroStation |
P522
|
FINISHED |
| Object |
Shuicheng Road Station
Shuicheng Road Station is a Shanghai Metro station serving the Changning District in Shanghai, China.
|
E282051
|
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: Shuicheng Road Station | Statement: [Changning District, hasMetroStation, Shuicheng Road Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shuicheng Road Station Context triple: [Changning District, hasMetroStation, Shuicheng Road Station]
-
A.
Dongchuan Road Station
Dongchuan Road Station is a Shanghai Metro station serving the Minhang District area of Shanghai, China.
-
B.
Lianhua Road Station
Lianhua Road Station is a Shanghai Metro station serving the Minhang District as part of the city’s rapid transit network.
-
C.
Jianchuan Road Station
Jianchuan Road Station is a Shanghai Metro station serving the Minhang District area of Shanghai, China.
-
D.
Loushanguan Road Station
Loushanguan Road Station is a Shanghai Metro station serving the Changning District area of Shanghai, China.
-
E.
Changshou Lu Station
Changshou Lu Station is an underground metro station on the Guangzhou Metro system serving the bustling Changshou Road commercial area in Guangzhou, 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: Shuicheng Road Station Triple: [Changning District, hasMetroStation, Shuicheng Road Station]
Generated description
Shuicheng Road Station is a Shanghai Metro station serving the Changning District in Shanghai, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shuicheng Road Station Target entity description: Shuicheng Road Station is a Shanghai Metro station serving the Changning District in Shanghai, China.
-
A.
Dongchuan Road Station
Dongchuan Road Station is a Shanghai Metro station serving the Minhang District area of Shanghai, China.
-
B.
Lianhua Road Station
Lianhua Road Station is a Shanghai Metro station serving the Minhang District as part of the city’s rapid transit network.
-
C.
Jianchuan Road Station
Jianchuan Road Station is a Shanghai Metro station serving the Minhang District area of Shanghai, China.
-
D.
Loushanguan Road Station
Loushanguan Road Station is a Shanghai Metro station serving the Changning District area of Shanghai, China.
-
E.
Changshou Lu Station
Changshou Lu Station is an underground metro station on the Guangzhou Metro system serving the bustling Changshou Road commercial area 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7bafa248190a68e8f1e081f4817 |
completed | March 7, 2026, 6:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af836559908190800f3be44aecd82f |
completed | March 10, 2026, 2:35 a.m. |
| NEDg | Description generation | batch_69af858124908190b2c717aa1a44ee33 |
completed | March 10, 2026, 2:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af86371b6c8190b17a7e57df9b4fb3 |
completed | March 10, 2026, 2:47 a.m. |
Created at: March 4, 2026, 7:57 p.m.