Triple
T16039251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daxing Line (Beijing Subway) |
E389049
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Xingong station
Xingong station is a subway station in Beijing that serves as a stop on the Daxing Line of the Beijing Subway system.
|
E1305262
|
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: Xingong station | Statement: [Daxing Line (Beijing Subway), hasStation, Xingong station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xingong station Context triple: [Daxing Line (Beijing Subway), hasStation, Xingong station]
-
A.
Yongning station
Yongning station is a metro station on Taipei's Bannan (Blue) Line serving the Tucheng District in New Taipei City, Taiwan.
-
B.
Sihui station
Sihui station is a Beijing Subway interchange station serving as a key transfer point between major urban rail lines in the city.
-
C.
Kunyang station
Kunyang station is a metro station on the Taipei Metro system in Taiwan, serving the Bannan line in the Nangang District.
-
D.
Zhichunlu station
Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
-
E.
Shichang station
Shichang station is a Beijing Subway station serving as the western terminus of the S1 Line in Beijing, China.
- 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: Xingong station Triple: [Daxing Line (Beijing Subway), hasStation, Xingong station]
Generated description
Xingong station is a subway station in Beijing that serves as a stop on the Daxing Line of the Beijing Subway system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xingong station Target entity description: Xingong station is a subway station in Beijing that serves as a stop on the Daxing Line of the Beijing Subway system.
-
A.
Yongning station
Yongning station is a metro station on Taipei's Bannan (Blue) Line serving the Tucheng District in New Taipei City, Taiwan.
-
B.
Sihui station
Sihui station is a Beijing Subway interchange station serving as a key transfer point between major urban rail lines in the city.
-
C.
Kunyang station
Kunyang station is a metro station on the Taipei Metro system in Taiwan, serving the Bannan line in the Nangang District.
-
D.
Zhichunlu station
Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
-
E.
Shichang station
Shichang station is a Beijing Subway station serving as the western terminus of the S1 Line in Beijing, China.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1833eb90c8190b10dca3ce0793ddf |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a035d724d588190a1fa67880c00a9cc |
completed | May 12, 2026, 5:03 p.m. |
| NEDg | Description generation | batch_6a036313d0f081908f6fd21f706e666d |
completed | May 12, 2026, 5:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0363640e34819091abe29dd1c96941 |
completed | May 12, 2026, 5:29 p.m. |
Created at: April 10, 2026, 4:56 a.m.