Triple
T3162014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Library station |
E66122
|
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: [National Library station, partOf, Beijing Subway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beijing Subway Context triple: [National Library 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.
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.
-
C.
Tianjin Metro
Tianjin Metro is the rapid transit system serving the city of Tianjin, China, providing urban and suburban rail transportation across the municipality.
-
D.
Shenzhen Metro
Shenzhen Metro is the rapid transit system serving the city of Shenzhen, China, known for its extensive, modern network and role in supporting the region’s fast-paced urban development.
-
E.
Shijiazhuang Metro
Shijiazhuang Metro is the rapid transit system serving the city of Shijiazhuang, providing urban rail transportation across the capital of Hebei Province in China.
- 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_69ad85850c1481908a9e9c6242238de2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada618b9b88190afaa6d47dcad9f2c |
completed | March 8, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3608e261081908b0633bf11ea655b |
completed | March 13, 2026, 12:55 a.m. |
Created at: March 8, 2026, 3:06 p.m.