Triple
T9912305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 1 (Guangzhou Metro) |
E185773
|
entity |
| Predicate | hasTerminus |
P388
|
FINISHED |
| Object |
Xilang station
Xilang station is a metro station in Guangzhou, China, serving as a terminus on the city's Line 1.
|
E854691
|
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: Xilang station | Statement: [Line 1 (Guangzhou Metro), hasTerminus, Xilang station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xilang station Context triple: [Line 1 (Guangzhou Metro), hasTerminus, Xilang station]
-
A.
Gangxia station
Gangxia station is a metro station in Shenzhen, China, serving as part of the city’s rapid transit network.
-
B.
Ximen Station
Ximen Station is a major Taipei Metro interchange station in the Ximending shopping and entertainment district of Taipei, Taiwan.
-
C.
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.
-
D.
Haizhu Square Station
Haizhu Square Station is a major underground metro station in central Guangzhou, China, serving as a key transit point near the Pearl River and the historic Haizhu Square area.
-
E.
Xicun Station
Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
- 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: Xilang station Triple: [Line 1 (Guangzhou Metro), hasTerminus, Xilang station]
Generated description
Xilang station is a metro station in Guangzhou, China, serving as a terminus on the city's Line 1.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xilang station Target entity description: Xilang station is a metro station in Guangzhou, China, serving as a terminus on the city's Line 1.
-
A.
Gangxia station
Gangxia station is a metro station in Shenzhen, China, serving as part of the city’s rapid transit network.
-
B.
Ximen Station
Ximen Station is a major Taipei Metro interchange station in the Ximending shopping and entertainment district of Taipei, Taiwan.
-
C.
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.
-
D.
Haizhu Square Station
Haizhu Square Station is a major underground metro station in central Guangzhou, China, serving as a key transit point near the Pearl River and the historic Haizhu Square area.
-
E.
Xicun Station
Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
- 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_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_69d71c3fa4b88190be4ce7b64335a99f |
completed | April 9, 2026, 3:25 a.m. |
| NEDg | Description generation | batch_69d71f76e3cc8190b21a5fe8825caa2b |
completed | April 9, 2026, 3:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d7319938ec8190a4a1a5f09832e3e3 |
completed | April 9, 2026, 4:56 a.m. |
Created at: March 30, 2026, 8:41 p.m.