Triple
T2055999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prasun language |
E45675
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Wasí-weri |
E228809
|
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: Wasí-weri | Statement: [Prasun language, alternativeName, Wasí-weri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wasí-weri Context triple: [Prasun language, alternativeName, Wasí-weri]
-
A.
Vasi-weri
chosen
Vasi-weri is an alternative name for the Prasun language, an Indo-Iranian language spoken in parts of Afghanistan.
-
B.
Warji
Warji is a Chadic language spoken primarily in northern Nigeria by the Warji people.
-
C.
Wadomari
Wadomari is a small coastal town on Okinoerabujima in Japan’s Kagoshima Prefecture, known for its subtropical climate and role as a local hub in the Amami archipelago.
-
D.
Wako
Wako is a suburban city in Saitama Prefecture, Japan, located on the northern outskirts of Tokyo and known as a residential and commuter hub.
-
E.
Oshiwambo
Oshiwambo is a Bantu language (or cluster of closely related dialects) widely spoken by the Ovambo people in northern Namibia and southern Angola.
- 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9a9ce548190a5a3488fafb2e79e |
completed | March 7, 2026, 5:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae271cb26c81908664f4c26f4fb5ea |
completed | March 9, 2026, 1:49 a.m. |
Created at: March 4, 2026, 7:40 p.m.