Triple
T15776552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tashkent Metro |
E382505
|
entity |
| Predicate | hasInterchangeStation |
P2413
|
FINISHED |
| Object | Paxtakor station |
E1176330
|
NE FINISHED |
How this triple was built (2 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: Paxtakor station | Statement: [Tashkent Metro, hasInterchangeStation, Paxtakor station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paxtakor station Context triple: [Tashkent Metro, hasInterchangeStation, Paxtakor station]
-
A.
Paxtakor station
chosen
Paxtakor station is a metro station in the Tashkent Metro system in Tashkent, Uzbekistan.
-
B.
Kaladar Station
Kaladar Station is a small rural community within the township of Addington Highlands in eastern Ontario, Canada.
-
C.
Kargar station
Kargar station is a metro stop on Tehran’s urban rail network serving passengers along Line 6.
-
D.
Chilonzor station
Chilonzor station is a metro station on the Tashkent Metro system in Tashkent, Uzbekistan.
-
E.
Hamar Station
Hamar Station is a railway station in the town of Hamar in Innlandet county, Norway, serving as a regional transport hub on the country’s rail network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ffa9361f5c8190b68702154d05bbc2 |
completed | May 9, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.