Triple
T6877872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norwegian education system |
E158715
|
entity |
| Predicate | supportsMinorityLanguage |
P22563
|
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: [Norwegian education system, supportsMinorityLanguage, Kven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kven Context triple: [Norwegian education system, supportsMinorityLanguage, Kven]
-
A.
Kven
chosen
Kven is a Finnic minority language closely related to Finnish, traditionally spoken by the Kven people in northern Norway.
-
B.
Kwan
Kwan is a Chinese-origin surname shared by many individuals, including the renowned American figure skater Michelle Kwan.
-
C.
Kuo
Kuo is a Wade–Giles romanization of the Chinese surname and name more commonly spelled "Guo" in pinyin.
-
D.
Wem
Wem is a small market town and civil parish in the county of Shropshire, England.
-
E.
QUEN
QUEN is the station code for Queen station, a public transit stop identified by this unique abbreviation.
- 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_69c68832af1481908ce356e133ebaebe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6e1cfd8fc81908efb83c061cb8e4f |
completed | March 27, 2026, 8 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c742c2b81881909bd13df0d6028cc6 |
completed | March 28, 2026, 2:53 a.m. |
Created at: March 27, 2026, 2:22 p.m.