Triple
T10815829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pamir Highway |
E255224
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Osh |
E318396
|
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: Osh | Statement: [Pamir Highway, connects, Osh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Osh Context triple: [Pamir Highway, connects, Osh]
-
A.
Osh
chosen
Osh is a major city in southern Kyrgyzstan, historically significant as a Silk Road trading center in the fertile Ferghana Valley.
-
B.
Oza
"Oza" is a prominent poetic work by Russian poet Andrei Voznesensky, reflecting his innovative style and experimental approach to verse.
-
C.
Osan
Osan is a city in Gyeonggi Province, South Korea, known for its proximity to Osan Air Base and its role as a regional transportation and commercial hub.
-
D.
Haruru
Haruru is a small settlement in New Zealand’s Bay of Islands region, known for its scenic surroundings and proximity to Haruru Falls.
-
E.
Ota
Ota is a historically significant Awori town in southwestern Nigeria that has grown into a major industrial and educational hub.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733edab248190b2cf7f7bc2684468 |
completed | April 9, 2026, 5:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de855799748190b51745a198daa8d0 |
completed | April 14, 2026, 6:20 p.m. |
Created at: April 8, 2026, 9:18 p.m.