Triple
T15197643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hepingmen station |
E363178
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Beijing Subway |
E12220
|
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: Beijing Subway | Statement: [Hepingmen station, partOf, Beijing Subway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beijing Subway Context triple: [Hepingmen station, partOf, Beijing Subway]
-
A.
Beijing Subway
chosen
The Beijing Subway is one of the world’s largest and busiest rapid transit systems, forming the backbone of public transportation in China’s capital city.
-
B.
Beijing MTR
Beijing MTR is a railway and metro operating company responsible for running several lines of the Beijing Subway in partnership with the city government.
-
C.
Shanghai Metro
Shanghai Metro is one of the world’s largest and busiest rapid transit systems, serving the city of Shanghai with an extensive network of urban and suburban rail lines.
-
D.
Beijing Suburban Railway
Beijing Suburban Railway is a commuter rail network serving the greater Beijing metropolitan area, connecting urban districts with surrounding suburban regions.
-
E.
Tianjin Metro
Tianjin Metro is the rapid transit system serving the city of Tianjin, China, providing urban and suburban rail transportation across the municipality.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b476208190a5119710c518bb1f |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef66b4f08190a072332123253166 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:10 a.m.