Triple
T10934030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peche Valley |
E258281
|
entity |
| Predicate | primaryHomelandOf |
P38603
|
FINISHED |
| Object | Ashkun speakers |
E45083
|
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 speakers | Statement: [Peche Valley, primaryHomelandOf, Ashkun speakers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashkun speakers Context triple: [Peche Valley, primaryHomelandOf, Ashkun speakers]
-
A.
Ashkun language
chosen
The Ashkun language is a Nuristani language spoken by the Ashkun people in remote regions of eastern Afghanistan.
-
B.
Akusha dialect
The Akusha dialect is a principal standardized variety of the Dargin language spoken in Dagestan, Russia.
-
C.
Asuri language
Asuri language is an endangered Munda language of the Austroasiatic family spoken by the Asur tribal community in eastern India, primarily in Jharkhand.
-
D.
Tashelhiyt
Tashelhiyt is a variety of the Shilha Berber language spoken primarily by Amazigh communities in southwestern Morocco.
-
E.
Anuki language
The Anuki language is an Oceanic language spoken by a small coastal community in Papua New Guinea’s Milne Bay Province.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770ae073881909720febe9f5f296a |
completed | April 9, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2176328448190bbce6735ec97507a |
completed | April 17, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:23 p.m.