Triple
T2236786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuristan Province |
E49298
|
entity |
| Predicate | hasEthnolinguisticGroup |
P1898
|
FINISHED |
| Object | Ashkun |
E228158
|
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: Ashkun | Statement: [Nuristan Province, hasEthnolinguisticGroup, Ashkun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashkun Context triple: [Nuristan Province, hasEthnolinguisticGroup, Ashkun]
-
A.
Ashkun
chosen
Ashkun is a Nuristani language spoken by the Ashkun people in parts of eastern Afghanistan.
-
B.
Akrosh
Akrosh is an Indian film best known as a hard-hitting social drama written by acclaimed playwright and screenwriter Vijay Tendulkar.
-
C.
Akhnur
Akhnur is a town in the Jammu district of the Indian union territory of Jammu and Kashmir, known for its strategic location near the India–Pakistan border and its historical and archaeological significance.
-
D.
Kadmat
Kadmat is a coral island in India’s Lakshadweep archipelago, known for its white-sand beaches, clear lagoons, and vibrant marine life that make it a popular destination for snorkeling and diving.
-
E.
Ashti
Ashti is a town in the Wardha district of Maharashtra, India, known primarily as a local administrative and agricultural center.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc09573848190bf91eddcc2fa0061 |
completed | March 7, 2026, 6:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6b08c5248190924a28f4c1bd0e2c |
completed | March 9, 2026, 6:39 a.m. |
Created at: March 4, 2026, 7:47 p.m.