Triple
T7217903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daegu Metro |
E150181
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Ansim Depot
Ansim Depot is a maintenance and storage facility serving the Daegu Metro system in Daegu, South Korea.
|
E649958
|
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: Ansim Depot | Statement: [Daegu Metro, hasDepot, Ansim Depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ansim Depot Context triple: [Daegu Metro, hasDepot, Ansim Depot]
-
A.
Vastral Depot
Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
-
B.
Pajura depot
Pajura depot is a maintenance and storage facility serving the Bucharest Metro system in Romania.
-
C.
Bümpliz depot
Bümpliz depot is a tram facility in the Bümpliz district of Bern used for housing, maintaining, and dispatching vehicles of the city’s tram network.
-
D.
Nopo Depot
Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
-
E.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
- 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: Ansim Depot Triple: [Daegu Metro, hasDepot, Ansim Depot]
Generated description
Ansim Depot is a maintenance and storage facility serving the Daegu Metro system in Daegu, South Korea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ansim Depot Target entity description: Ansim Depot is a maintenance and storage facility serving the Daegu Metro system in Daegu, South Korea.
-
A.
Vastral Depot
Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
-
B.
Pajura depot
Pajura depot is a maintenance and storage facility serving the Bucharest Metro system in Romania.
-
C.
Bümpliz depot
Bümpliz depot is a tram facility in the Bümpliz district of Bern used for housing, maintaining, and dispatching vehicles of the city’s tram network.
-
D.
Nopo Depot
Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
-
E.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
- 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e99170d88190b1aef326a7d81134 |
completed | March 27, 2026, 8:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cbfb46388190992cc98039e71748 |
completed | March 28, 2026, 12:39 p.m. |
| NEDg | Description generation | batch_69c7cce6a290819096ff68333cd3a3cf |
completed | March 28, 2026, 12:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7cd9966e481909eb3c23bb59777d9 |
completed | March 28, 2026, 12:46 p.m. |
Created at: March 27, 2026, 2:53 p.m.