Triple
T14401328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kainun institutti |
E357076
|
entity |
| Predicate | languageOfWorkOrName |
P15
|
FINISHED |
| Object | Kven |
E74948
|
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: Kven | Statement: [Kainun institutti, languageOfWorkOrName, Kven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kven Context triple: [Kainun institutti, languageOfWorkOrName, Kven]
-
A.
Kven
chosen
Kven is a Finnic minority language closely related to Finnish, traditionally spoken by the Kven people in northern Norway.
-
B.
Koho
Koho is an Austroasiatic language spoken by the Koho ethnic group in Vietnam’s Central Highlands.
-
C.
Kwan
Kwan is a Chinese-origin surname shared by many individuals, including the renowned American figure skater Michelle Kwan.
-
D.
Kuo
Kuo is a Wade–Giles romanization of the Chinese surname and name more commonly spelled "Guo" in pinyin.
-
E.
Wem
Wem is a small market town and civil parish in the county of Shropshire, England.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de908500048190bb6a20fe318d5c62 |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5520c07c8190bfdaf224dd779ced |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:17 a.m.