Triple
T15776489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tashkent railway station |
E382504
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | city of Tashkent |
E81695
|
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: city of Tashkent | Statement: [Tashkent railway station, serves, city of Tashkent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: city of Tashkent Context triple: [Tashkent railway station, serves, city of Tashkent]
-
A.
Tashkent
chosen
Tashkent is the capital and largest city of Uzbekistan, a major cultural and economic hub in Central Asia with deep historical ties to the Islamic world.
-
B.
Taşkent
Taşkent is a small mountainous district and town in Turkey’s Konya Province, known for its rural character and scenic Anatolian landscape.
-
C.
Navoi
Navoi is an industrial city in central Uzbekistan known for its mining, metallurgy, and chemical industries.
-
D.
Bukhara, Uzbekistan
Bukhara, Uzbekistan is an ancient Silk Road city renowned for its well-preserved Islamic architecture and historic center, a UNESCO World Heritage Site.
-
E.
Yoshkar-Ola
Yoshkar-Ola is a city in central Russia that serves as the administrative, cultural, and economic center of the Mari El Republic.
- 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.