Triple
T7038422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bohuslän |
E163444
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Skärhamn
Skärhamn is a coastal town in western Sweden known for its fishing heritage, picturesque harbor, and the Nordic Watercolour Museum.
|
E640835
|
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: Skärhamn | Statement: [Bohuslän, containsTown, Skärhamn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skärhamn Context triple: [Bohuslän, containsTown, Skärhamn]
-
A.
Fredrikshamn
Fredrikshamn (Hamina) is a coastal town in southeastern Finland that historically served as an important military and trading center.
-
B.
Skärholmen
Skärholmen is a suburban district in southwestern Stockholm, Sweden, known for its large shopping center and residential areas.
-
C.
Skarpö
Skarpö is an island in the Stockholm archipelago of Sweden, situated within Vaxholm Municipality and known for its coastal scenery and residential character.
-
D.
Värtahamnen
Värtahamnen is a major port and harbor area in Stockholm, Sweden, serving as an important hub for ferry, cargo, and cruise traffic in the Baltic Sea region.
-
E.
Västerljung
Västerljung is a small locality in eastern Sweden situated within Trosa Municipality in Södermanland County.
- 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: Skärhamn Triple: [Bohuslän, containsTown, Skärhamn]
Generated description
Skärhamn is a coastal town in western Sweden known for its fishing heritage, picturesque harbor, and the Nordic Watercolour Museum.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Skärhamn Target entity description: Skärhamn is a coastal town in western Sweden known for its fishing heritage, picturesque harbor, and the Nordic Watercolour Museum.
-
A.
Fredrikshamn
Fredrikshamn (Hamina) is a coastal town in southeastern Finland that historically served as an important military and trading center.
-
B.
Skärholmen
Skärholmen is a suburban district in southwestern Stockholm, Sweden, known for its large shopping center and residential areas.
-
C.
Skarpö
Skarpö is an island in the Stockholm archipelago of Sweden, situated within Vaxholm Municipality and known for its coastal scenery and residential character.
-
D.
Värtahamnen
Värtahamnen is a major port and harbor area in Stockholm, Sweden, serving as an important hub for ferry, cargo, and cruise traffic in the Baltic Sea region.
-
E.
Västerljung
Västerljung is a small locality in eastern Sweden situated within Trosa Municipality in Södermanland County.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e223077c819097992089fa83c563 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7943fe4fc819087bbcc724deed80a |
completed | March 28, 2026, 8:41 a.m. |
| NEDg | Description generation | batch_69c7967dd32081908ad7cca8bd4ec7e4 |
completed | March 28, 2026, 8:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c797666b688190918d9b158de09af8 |
completed | March 28, 2026, 8:55 a.m. |
Created at: March 27, 2026, 2:36 p.m.