Triple
T21458055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E60 |
E529392
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Dushanbe |
—
|
NE NERFINISHED |
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: Dushanbe | Statement: [E60, passesThrough, Dushanbe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dushanbe Context triple: [E60, passesThrough, Dushanbe]
-
A.
Dushanbe
chosen
Dushanbe is the largest city and political, economic, and cultural center of Tajikistan.
-
B.
Khorog
Khorog is a remote mountain town in eastern Tajikistan that serves as the capital of the Gorno-Badakhshan Autonomous Region and a key hub in the Pamir Mountains.
-
C.
Tokmok
Tokmok is a small city in northern Kyrgyzstan, near the border with Kazakhstan, known as an industrial and agricultural center in the Chüy Valley.
-
D.
Tashkent
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.
-
E.
Tashkurgan
Tashkurgan is a remote town in China’s Xinjiang region, inhabited mainly by Tajik people and known as a key stop on the Karakoram Highway near the Pakistan border.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c458133481908ae8b41a12c4edec |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9ec254081909a703056022f4f45 |
completed | April 23, 2026, 9:44 a.m. |
Created at: April 16, 2026, 6:08 p.m.