Triple
T8674770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawrami dialect |
E205886
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Hewrami |
E205883
|
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: Hewrami | Statement: [Hawrami dialect, hasAlternativeName, Hewrami]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hewrami Context triple: [Hawrami dialect, hasAlternativeName, Hewrami]
-
A.
Hewrami
chosen
Hewrami is a dialect of the Gorani branch of Northwestern Iranian languages, traditionally spoken by Kurdish communities in the Hawraman region of western Iran and northeastern Iraq.
-
B.
Sako
Sako is a Finnish firearms manufacturer renowned for its high-quality rifles and precision engineering, operating as a subsidiary of Beretta.
-
C.
Tikka
Tikka is a Finnish firearms manufacturer best known for producing high-quality, accurate bolt-action rifles, and operates as a brand under Beretta’s corporate group.
-
D.
Mosina
Mosina is an alternative name for Vurës, a language spoken on the island of Vanua Lava in Vanuatu.
-
E.
Aasrud
Aasrud is a Norwegian surname most notably borne by politician Rigmor Aasrud.
- 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_69ca83529a9c8190b5c075b4f14636ed |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc491cee048190a6f6cddabada76dc |
completed | March 31, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cecd4719a881908ee6bd8514ab9f81 |
completed | April 2, 2026, 8:10 p.m. |
Created at: March 30, 2026, 6:31 p.m.