Triple
T13799323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Vänern |
E331596
|
entity |
| Predicate | hasCityOnShore |
P969
|
FINISHED |
| Object |
Åmål
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).
|
E1062003
|
NE FINISHED |
How this triple was built (4 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: [Lake Vänern, hasCityOnShore, Åmål]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Åmål Context triple: [Lake Vänern, hasCityOnShore, Åmål]
-
A.
Åmli
Åmli is a rural municipality in Agder county in southern Norway, known for its forested landscapes, rivers, and outdoor recreation opportunities.
-
B.
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.
-
C.
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.
-
D.
Åshammar
Åshammar is a small locality in central Sweden situated within Gävleborg County.
-
E.
Ahlmark
Ahlmark is a Swedish surname most notably associated with Per Ahlmark, a prominent Swedish politician, writer, and former Deputy Prime Minister.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Åmål Triple: [Lake Vänern, hasCityOnShore, Åmål]
Generated description
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).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Åmål Target entity description: 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).
-
A.
Åmli
Åmli is a rural municipality in Agder county in southern Norway, known for its forested landscapes, rivers, and outdoor recreation opportunities.
-
B.
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.
-
C.
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.
-
D.
Åshammar
Åshammar is a small locality in central Sweden situated within Gävleborg County.
-
E.
Ahlmark
Ahlmark is a Swedish surname most notably associated with Per Ahlmark, a prominent Swedish politician, writer, and former Deputy Prime Minister.
- F. None of above. chosen
Provenance (5 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025ce9148190b23370f6a522ff7a |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0893a20819081d4001b8dbc9c36 |
completed | May 3, 2026, 8:31 p.m. |
| NEDg | Description generation | batch_69f7b138fda88190b2b7ffb51ce02a40 |
completed | May 3, 2026, 8:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7b28ca218819097fc35042d3b278a |
completed | May 3, 2026, 8:39 p.m. |
Created at: April 9, 2026, 10:11 p.m.