Triple
T1710906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Busan Metro |
E36979
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Nopo Depot
Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
|
E193676
|
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: Nopo Depot | Statement: [Busan Metro, hasDepot, Nopo Depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nopo Depot Context triple: [Busan Metro, hasDepot, Nopo Depot]
-
A.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
B.
Pontinha depot
Pontinha depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
C.
Fürth depot
Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
-
D.
Wellington Yard
Wellington Yard is a railway yard associated with Wellington station, used for storing, organizing, and managing trains and rolling stock.
-
E.
Kelso Depot
Kelso Depot is a historic former railroad station and visitor center in California’s Mojave Desert, notable for its Spanish Mission Revival architecture and role in serving travelers and workers along the Union Pacific Railroad.
- 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: Nopo Depot Triple: [Busan Metro, hasDepot, Nopo Depot]
Generated description
Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nopo Depot Target entity description: Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
-
A.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
B.
Pontinha depot
Pontinha depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
C.
Fürth depot
Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
-
D.
Wellington Yard
Wellington Yard is a railway yard associated with Wellington station, used for storing, organizing, and managing trains and rolling stock.
-
E.
Kelso Depot
Kelso Depot is a historic former railroad station and visitor center in California’s Mojave Desert, notable for its Spanish Mission Revival architecture and role in serving travelers and workers along the Union Pacific Railroad.
- 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_69a88617439c819094ffb5d16a0f6307 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa63149288819082e7055d0d292d1d |
completed | March 6, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8addf4a48190b19cdb861db5eecd |
completed | March 8, 2026, 2:42 p.m. |
| NEDg | Description generation | batch_69ad957912808190be5b6ed8d3f20535 |
completed | March 8, 2026, 3:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad97accca48190bc43e94337589a5f |
completed | March 8, 2026, 3:37 p.m. |
Created at: March 4, 2026, 7:30 p.m.