Triple
T9912309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 1 (Guangzhou Metro) |
E185773
|
entity |
| Predicate | servesStation |
P839
|
FINISHED |
| Object | Huangsha station |
E214246
|
NE FINISHED |
How this triple was built (2 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: Huangsha station | Statement: [Line 1 (Guangzhou Metro), servesStation, Huangsha station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huangsha station Context triple: [Line 1 (Guangzhou Metro), servesStation, Huangsha station]
-
A.
Huangsha Station
chosen
Huangsha Station is a metro station in Guangzhou, China, serving as part of the city's Guangzhou Metro rapid transit network.
-
B.
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.
-
C.
Wujiaochang station
Wujiaochang station is a Shanghai Metro station serving the busy Wujiaochang commercial and university district in Yangpu District.
-
D.
Tiantongyuan station
Tiantongyuan station is a subway station in Beijing, China, serving the northern residential area of Tiantongyuan on the city's metro network.
-
E.
Baishizhou station
Baishizhou station is a metro station in Shenzhen, China, serving the densely populated Baishizhou area and nearby attractions such as Window of the World.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca829b45f481909040f7b99a1976ed |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb5391b8081908094b88cdde4b55a |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fb12ac9c819087a182c12653792c |
completed | April 9, 2026, 7:16 p.m. |
Created at: March 30, 2026, 8:41 p.m.