Triple
T7604708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gjesdal |
E180071
|
entity |
| Predicate | administrativeCentre |
P1474
|
FINISHED |
| Object |
Ålgård
Ålgård is a village in Rogaland county, Norway, known as a growing residential and industrial community just south of Sandnes.
|
E676283
|
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: Ålgård | Statement: [Gjesdal, administrativeCentre, Ålgård]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ålgård Context triple: [Gjesdal, administrativeCentre, Ålgård]
-
A.
Ålsgårde
Ålsgårde is a coastal town in North Zealand, Denmark, known for its residential areas and proximity to the Øresund Strait.
-
B.
Ulriksdal
Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
-
C.
Nordingrå
Nordingrå is a small locality in Sweden’s High Coast region, known for its coastal landscapes and traditional rural communities.
-
D.
Norsborg
Norsborg is a suburban district in Botkyrka Municipality, southwest of central Stockholm, Sweden, known as the terminus area of the Stockholm metro’s red line.
-
E.
Fagerborg
Fagerborg is a residential neighborhood in Oslo, Norway, known for its central location, historic buildings, and proximity to major educational institutions.
- 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: Ålgård Triple: [Gjesdal, administrativeCentre, Ålgård]
Generated description
Ålgård is a village in Rogaland county, Norway, known as a growing residential and industrial community just south of Sandnes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ålgård Target entity description: Ålgård is a village in Rogaland county, Norway, known as a growing residential and industrial community just south of Sandnes.
-
A.
Ålsgårde
Ålsgårde is a coastal town in North Zealand, Denmark, known for its residential areas and proximity to the Øresund Strait.
-
B.
Ulriksdal
Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
-
C.
Nordingrå
Nordingrå is a small locality in Sweden’s High Coast region, known for its coastal landscapes and traditional rural communities.
-
D.
Norsborg
Norsborg is a suburban district in Botkyrka Municipality, southwest of central Stockholm, Sweden, known as the terminus area of the Stockholm metro’s red line.
-
E.
Fagerborg
Fagerborg is a residential neighborhood in Oslo, Norway, known for its central location, historic buildings, and proximity to major educational institutions.
- 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_69c69f3567008190ab01d2ca7b53584a |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9fbd1408190b721bf016f997c7b |
completed | March 27, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c86853e1fc8190b16cdf779057c804 |
completed | March 28, 2026, 11:46 p.m. |
| NEDg | Description generation | batch_69c868fb7fe48190a1b7ab0e824e2984 |
completed | March 28, 2026, 11:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8697782d48190a6830f91800d3505 |
completed | March 28, 2026, 11:51 p.m. |
Created at: March 27, 2026, 3:54 p.m.