Triple
T6714691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaxön |
E153236
|
entity |
| Predicate | hasNearbyIsland |
P970
|
FINISHED |
| Object |
Stegesund
Stegesund is a small island in the Stockholm archipelago of Sweden, known for its scenic coastal setting and proximity to the town of Vaxholm.
|
E613245
|
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: Stegesund | Statement: [Vaxön, hasNearbyIsland, Stegesund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stegesund Context triple: [Vaxön, hasNearbyIsland, Stegesund]
-
A.
Stordal
Stordal is a small village and former municipality in western Norway, known for its scenic fjord landscape and traditional Norwegian architecture.
-
B.
Gangstad
Gangstad is a small settlement located within the municipality of Inderøy in Trøndelag county, Norway.
-
C.
Stabekk
Stabekk is a suburban area in Bærum, Norway, known for its residential neighborhoods, proximity to Oslo, and good transport connections.
-
D.
Storslett
Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
-
E.
Sundvollen
Sundvollen is a small village in Norway known for its scenic location by Tyrifjorden and as a gateway to popular hiking areas like Krokskogen and viewpoints such as Kongens utsikt.
- 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: Stegesund Triple: [Vaxön, hasNearbyIsland, Stegesund]
Generated description
Stegesund is a small island in the Stockholm archipelago of Sweden, known for its scenic coastal setting and proximity to the town of Vaxholm.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stegesund Target entity description: Stegesund is a small island in the Stockholm archipelago of Sweden, known for its scenic coastal setting and proximity to the town of Vaxholm.
-
A.
Stordal
Stordal is a small village and former municipality in western Norway, known for its scenic fjord landscape and traditional Norwegian architecture.
-
B.
Gangstad
Gangstad is a small settlement located within the municipality of Inderøy in Trøndelag county, Norway.
-
C.
Stabekk
Stabekk is a suburban area in Bærum, Norway, known for its residential neighborhoods, proximity to Oslo, and good transport connections.
-
D.
Storslett
Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
-
E.
Sundvollen
Sundvollen is a small village in Norway known for its scenic location by Tyrifjorden and as a gateway to popular hiking areas like Krokskogen and viewpoints such as Kongens utsikt.
- 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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d122d6cc81909bde0c94fb95f016 |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70096e05c8190abfa90996db37eeb |
completed | March 27, 2026, 10:11 p.m. |
| NEDg | Description generation | batch_69c701fa048c819091585d2bd4afe06a |
completed | March 27, 2026, 10:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7028710788190b054c7cfd28a6812 |
completed | March 27, 2026, 10:19 p.m. |
Created at: March 27, 2026, 2:07 p.m.