Triple
T19155357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bromma |
E468914
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Höglandet
Höglandet is a residential neighborhood in the Bromma district of western Stockholm, Sweden, known for its green areas and suburban character.
|
E1361750
|
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: Höglandet | Statement: [Bromma, contains, Höglandet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Höglandet Context triple: [Bromma, contains, Höglandet]
-
A.
Høylandet
Høylandet is a rural municipality in Trøndelag county, Norway, known for its forested landscapes, agriculture, and small village communities.
-
B.
Grossgrunden
Grossgrunden is one of the islands in the Holmön archipelago off the coast of northern Sweden in the Gulf of Bothnia.
-
C.
Hurumlandet
Hurumlandet is a peninsula in Viken county, Norway, known for its coastal landscapes along the Oslofjord and Drammensfjord.
-
D.
Berg en Dal
Berg en Dal is a Dutch municipality in the province of Gelderland, known for its hilly landscape, forests, and proximity to the city of Nijmegen.
-
E.
Högdalen
Högdalen is a suburban district in southern Stockholm, Sweden, known for its residential areas and local shopping center.
- 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: Höglandet Triple: [Bromma, contains, Höglandet]
Generated description
Höglandet is a residential neighborhood in the Bromma district of western Stockholm, Sweden, known for its green areas and suburban character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Höglandet Target entity description: Höglandet is a residential neighborhood in the Bromma district of western Stockholm, Sweden, known for its green areas and suburban character.
-
A.
Høylandet
Høylandet is a rural municipality in Trøndelag county, Norway, known for its forested landscapes, agriculture, and small village communities.
-
B.
Grossgrunden
Grossgrunden is one of the islands in the Holmön archipelago off the coast of northern Sweden in the Gulf of Bothnia.
-
C.
Hurumlandet
Hurumlandet is a peninsula in Viken county, Norway, known for its coastal landscapes along the Oslofjord and Drammensfjord.
-
D.
Berg en Dal
Berg en Dal is a Dutch municipality in the province of Gelderland, known for its hilly landscape, forests, and proximity to the city of Nijmegen.
-
E.
Högdalen
Högdalen is a suburban district in southern Stockholm, Sweden, known for its residential areas and local shopping center.
- 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5eeb914248190a92dc5f30cbc8fcc |
completed | April 20, 2026, 9:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a06f258c5a0819084921b6e44bf1b34 |
completed | May 15, 2026, 10:15 a.m. |
| NEDg | Description generation | batch_6a06f41269748190b6fa6301d8eb4f4f |
completed | May 15, 2026, 10:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a06f4da6b04819084dab89e9b3c5d3e |
completed | May 15, 2026, 10:26 a.m. |
Created at: April 10, 2026, 12:06 p.m.