Triple
T13824355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 4 (Beijing Subway) |
E332211
|
entity |
| Predicate | servesStation |
P839
|
FINISHED |
| Object | Xizhimen station |
E68686
|
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: Xizhimen station | Statement: [Line 4 (Beijing Subway), servesStation, Xizhimen station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xizhimen station Context triple: [Line 4 (Beijing Subway), servesStation, Xizhimen station]
-
A.
Xizhimen station
chosen
Xizhimen station is a major interchange hub in the Beijing Subway system, connecting multiple lines and serving the busy Xizhimen commercial and transport area.
-
B.
Chongwenmen station
Chongwenmen station is a major interchange stop on the Beijing Subway serving central Beijing near the historic Chongwenmen gate area.
-
C.
Xuanwumen station
Xuanwumen station is a major interchange stop on the Beijing Subway, serving as a key transfer point near central Beijing.
-
D.
Fuxingmen station
Fuxingmen station is a major interchange stop on the Beijing Subway, serving as a key transfer point between multiple central city lines.
-
E.
Dongzhimen station
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.
- 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_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_69fd6474da3081909be6b892ef8cc73e |
completed | May 8, 2026, 4:20 a.m. |
Created at: April 9, 2026, 10:13 p.m.