Triple
T13824451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 1 (Beijing Subway) |
E332214
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Babaoshan station
Babaoshan station is a Beijing Subway station on the city's Line 1, serving the Babaoshan area in western Beijing.
|
E1123270
|
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: Babaoshan station | Statement: [Line 1 (Beijing Subway), hasStation, Babaoshan station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Babaoshan station Context triple: [Line 1 (Beijing Subway), hasStation, Babaoshan station]
-
A.
Nanpu station
Nanpu station is a metro station in Guangzhou, China, serving passengers on the city’s Line 2 rapid transit route.
-
B.
Hongqiao Road Station
Hongqiao Road Station is a major Shanghai Metro interchange station serving multiple lines in the western part of the city.
-
C.
Chunxi Road Station
Chunxi Road Station is a major metro station in Chengdu, China, providing access to the popular commercial and shopping district around Chunxi Road.
-
D.
Dongsi station
Dongsi station is a Beijing Subway interchange station in central Beijing that serves both Line 5 and Line 6.
-
E.
Beixinjing Station
Beixinjing Station is a Shanghai Metro station serving the Beixinjing area in the city's Changning District.
- 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: Babaoshan station Triple: [Line 1 (Beijing Subway), hasStation, Babaoshan station]
Generated description
Babaoshan station is a Beijing Subway station on the city's Line 1, serving the Babaoshan area in western Beijing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Babaoshan station Target entity description: Babaoshan station is a Beijing Subway station on the city's Line 1, serving the Babaoshan area in western Beijing.
-
A.
Nanpu station
Nanpu station is a metro station in Guangzhou, China, serving passengers on the city’s Line 2 rapid transit route.
-
B.
Hongqiao Road Station
Hongqiao Road Station is a major Shanghai Metro interchange station serving multiple lines in the western part of the city.
-
C.
Chunxi Road Station
Chunxi Road Station is a major metro station in Chengdu, China, providing access to the popular commercial and shopping district around Chunxi Road.
-
D.
Dongsi station
Dongsi station is a Beijing Subway interchange station in central Beijing that serves both Line 5 and Line 6.
-
E.
Beixinjing Station
Beixinjing Station is a Shanghai Metro station serving the Beixinjing area in the city's Changning District.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0285fb7c8190be4b90bdc0d6fa53 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe64e47f1c8190a4ad09bc96d35b69 |
completed | May 8, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_69fe664fe96081908ca0923791bd212b |
completed | May 8, 2026, 10:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe66be64808190bab35f07d556d446 |
completed | May 8, 2026, 10:42 p.m. |
Created at: April 9, 2026, 10:13 p.m.