Triple
T3750492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troms og Finnmark |
E81316
|
entity |
| Predicate | hasRecognizedMinorityLanguage |
P2267
|
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: [Troms og Finnmark, hasRecognizedMinorityLanguage, Kven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kven Context triple: [Troms og Finnmark, hasRecognizedMinorityLanguage, 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.
Wem
Wem is a small market town and civil parish in the county of Shropshire, England.
-
D.
QUEN
QUEN is the station code for Queen station, a public transit stop identified by this unique abbreviation.
-
E.
Hven
Hven is a small Danish island in the Øresund Strait, historically renowned as the site of astronomer Tycho Brahe’s pioneering observatories and research center.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb6d0ac4819092c9a41cc60f518d |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db34aa5c8190ba3f22ee0f1f4208 |
completed | March 14, 2026, 3:51 a.m. |
Created at: March 8, 2026, 3:35 p.m.