Triple
T15777632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baku Metro |
E382528
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Narimanov depot
Narimanov depot is a major maintenance and storage facility serving the Baku Metro system in Baku, Azerbaijan.
|
E1177397
|
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: Narimanov depot | Statement: [Baku Metro, hasDepot, Narimanov depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Narimanov depot Context triple: [Baku Metro, hasDepot, Narimanov depot]
-
A.
Moskovskoe depot
Moskovskoe depot is a maintenance and storage facility serving the Minsk Metro system in Minsk, Belarus.
-
B.
Vykhino depot
Vykhino depot is a maintenance and storage facility serving trains of the Tagansko–Krasnopresnenskaya Line of the Moscow Metro.
-
C.
Kholodna Hora depot
Kholodna Hora depot is a maintenance and storage facility serving the Kharkiv Metro system in Kharkiv, Ukraine.
-
D.
Panfilovskaya MCC station
Panfilovskaya MCC station is a passenger railway station on Moscow’s urban rail network, serving the Moscow Central Circle line as part of the city’s integrated public transit system.
-
E.
Zavod Barrikady station
Zavod Barrikady station is a stop on the Volgograd Metrotram system in Volgograd, Russia, serving the industrial area around the historic Barrikady factory.
- 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: Narimanov depot Triple: [Baku Metro, hasDepot, Narimanov depot]
Generated description
Narimanov depot is a major maintenance and storage facility serving the Baku Metro system in Baku, Azerbaijan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Narimanov depot Target entity description: Narimanov depot is a major maintenance and storage facility serving the Baku Metro system in Baku, Azerbaijan.
-
A.
Moskovskoe depot
Moskovskoe depot is a maintenance and storage facility serving the Minsk Metro system in Minsk, Belarus.
-
B.
Vykhino depot
Vykhino depot is a maintenance and storage facility serving trains of the Tagansko–Krasnopresnenskaya Line of the Moscow Metro.
-
C.
Kholodna Hora depot
Kholodna Hora depot is a maintenance and storage facility serving the Kharkiv Metro system in Kharkiv, Ukraine.
-
D.
Panfilovskaya MCC station
Panfilovskaya MCC station is a passenger railway station on Moscow’s urban rail network, serving the Moscow Central Circle line as part of the city’s integrated public transit system.
-
E.
Zavod Barrikady station
Zavod Barrikady station is a stop on the Volgograd Metrotram system in Volgograd, Russia, serving the industrial area around the historic Barrikady factory.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05199cd8881909462462cec34d35a |
completed | April 16, 2026, 3:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff909d7b7c81908b62faa2ab378fad |
completed | May 9, 2026, 7:53 p.m. |
| NEDg | Description generation | batch_69ff9414408c8190903421d28519d9e6 |
completed | May 9, 2026, 8:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff9498642081909fd617a327b4c704 |
completed | May 9, 2026, 8:10 p.m. |
Created at: April 10, 2026, 4:47 a.m.