Triple
T10669524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dongdan |
E251449
|
entity |
| Predicate | hasTransportNode |
P2413
|
FINISHED |
| Object |
Dongdan Station
Dongdan Station is a major Beijing Subway interchange station serving as a key transfer point between central city lines.
|
E880026
|
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: Dongdan Station | Statement: [Dongdan, hasTransportNode, Dongdan Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dongdan Station Context triple: [Dongdan, hasTransportNode, Dongdan Station]
-
A.
Dongsi station
Dongsi station is a Beijing Subway interchange station in central Beijing that serves both Line 5 and Line 6.
-
B.
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.
-
C.
Chongwenmen station
Chongwenmen station is a major interchange stop on the Beijing Subway serving central Beijing near the historic Chongwenmen gate area.
-
D.
Baliqiao Station
Baliqiao Station is a stop on Beijing’s Batong Line, serving passengers in the eastern part of the city’s subway network.
-
E.
Hanyang Railway Station
Hanyang Railway Station is a major transport hub in Wuhan, China, serving both mainline rail services and the city’s metro network.
- 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: Dongdan Station Triple: [Dongdan, hasTransportNode, Dongdan Station]
Generated description
Dongdan Station is a major Beijing Subway interchange station serving as a key transfer point between central city lines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dongdan Station Target entity description: Dongdan Station is a major Beijing Subway interchange station serving as a key transfer point between central city lines.
-
A.
Dongsi station
Dongsi station is a Beijing Subway interchange station in central Beijing that serves both Line 5 and Line 6.
-
B.
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.
-
C.
Chongwenmen station
Chongwenmen station is a major interchange stop on the Beijing Subway serving central Beijing near the historic Chongwenmen gate area.
-
D.
Baliqiao Station
Baliqiao Station is a stop on Beijing’s Batong Line, serving passengers in the eastern part of the city’s subway network.
-
E.
Hanyang Railway Station
Hanyang Railway Station is a major transport hub in Wuhan, China, serving both mainline rail services and the city’s metro network.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6f861513881909b44c711371086b7 |
completed | April 9, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d998b77db08190bce5a7ce24dbc085 |
completed | April 11, 2026, 12:41 a.m. |
| NEDg | Description generation | batch_69d99e8312188190bec3090f34a7b9b9 |
completed | April 11, 2026, 1:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d99f50e0888190b8e7b2547e1526af |
completed | April 11, 2026, 1:09 a.m. |
Created at: April 8, 2026, 9:09 p.m.