Triple
T3176508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 13 (Beijing Subway) |
E66476
|
entity |
| Predicate | hasTerminus |
P388
|
FINISHED |
| Object | Dongzhimen station |
E68474
|
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: Dongzhimen station | Statement: [Line 13 (Beijing Subway), hasTerminus, Dongzhimen station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dongzhimen station Context triple: [Line 13 (Beijing Subway), hasTerminus, Dongzhimen station]
-
A.
Dongzhimen station
chosen
Dongzhimen station is a major Beijing Subway interchange hub connecting multiple lines and serving as a key gateway to the city’s northeastern districts and the airport rail link.
-
B.
Chaoyangmen station
Chaoyangmen station is a major interchange stop on the Beijing Subway serving the central Chaoyangmen area of Beijing.
-
C.
Fuxingmen station
Fuxingmen station is a major interchange stop on the Beijing Subway, serving as a key transfer point between multiple central city lines.
-
D.
Chongwenmen station
Chongwenmen station is a major interchange stop on the Beijing Subway serving central Beijing near the historic Chongwenmen gate area.
-
E.
Fuchengmen station
Fuchengmen station is an underground metro station in Beijing serving the central Xicheng District as part of the city’s extensive subway network.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada69b0bec8190957913b44d876079 |
completed | March 8, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e4b6ef4c81908a6861cba2a73652 |
completed | March 14, 2026, 10:44 p.m. |
Created at: March 8, 2026, 3:06 p.m.