Triple
T14881768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalsland |
E350016
|
entity |
| Predicate | largestTown |
P235
|
FINISHED |
| Object | Åmål |
E1062003
|
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: Åmål | Statement: [Dalsland, largestTown, Åmål]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Åmål Context triple: [Dalsland, largestTown, Åmål]
-
A.
Åmål
chosen
Åmål is a small town in western Sweden known for its picturesque lakeside setting and as the backdrop of the film "Show Me Love" (Fucking Åmål).
-
B.
Åmli
Åmli is a rural municipality in Agder county in southern Norway, known for its forested landscapes, rivers, and outdoor recreation opportunities.
-
C.
Hälsingemål
Hälsingemål is a Swedish dialect traditionally spoken in the Hälsingland region of Sweden, characterized by distinctive pronunciation, vocabulary, and grammar within the North Swedish dialect group.
-
D.
Sandvika
Sandvika is a town in southeastern Norway that serves as the administrative center of Bærum and a commercial hub in the Greater Oslo Region.
-
E.
Åshammar
Åshammar is a small locality in central Sweden situated within Gävleborg County.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e7c0e48190af2d68a71130585c |
completed | April 15, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b591f3c81909ea8a9217d96e0d2 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 1:56 a.m.