Triple
T8770751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Høvelte |
E208452
|
entity |
| Predicate | hasTransportConnection |
P845
|
FINISHED |
| Object |
Høvelte railway halt
Høvelte railway halt is a small local train stop in Denmark serving the Høvelte area on the regional rail network.
|
E757849
|
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: Høvelte railway halt | Statement: [Høvelte, hasTransportConnection, Høvelte railway halt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Høvelte railway halt Context triple: [Høvelte, hasTransportConnection, Høvelte railway halt]
-
A.
Hokksund Station
Hokksund Station is a railway station in Hokksund, Norway, serving as a local and regional transport hub on the country’s rail network.
-
B.
Veitvet station
Veitvet station is a metro stop in Oslo, Norway, located in the Veitvet neighborhood and forming part of the city's rapid transit network.
-
C.
Hellerud station
Hellerud station is a metro station in Oslo, Norway, serving as a junction on the city's eastern subway network.
-
D.
Henriksdal station
Henriksdal station is a commuter rail stop in the Stockholm area that serves passengers on the Saltsjöbanan line.
-
E.
Vollebekk station
Vollebekk station is a metro stop in Oslo, Norway, located on the city's rapid transit network and serving the surrounding residential area.
- 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: Høvelte railway halt Triple: [Høvelte, hasTransportConnection, Høvelte railway halt]
Generated description
Høvelte railway halt is a small local train stop in Denmark serving the Høvelte area on the regional rail network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Høvelte railway halt Target entity description: Høvelte railway halt is a small local train stop in Denmark serving the Høvelte area on the regional rail network.
-
A.
Hokksund Station
Hokksund Station is a railway station in Hokksund, Norway, serving as a local and regional transport hub on the country’s rail network.
-
B.
Veitvet station
Veitvet station is a metro stop in Oslo, Norway, located in the Veitvet neighborhood and forming part of the city's rapid transit network.
-
C.
Hellerud station
Hellerud station is a metro station in Oslo, Norway, serving as a junction on the city's eastern subway network.
-
D.
Henriksdal station
Henriksdal station is a commuter rail stop in the Stockholm area that serves passengers on the Saltsjöbanan line.
-
E.
Vollebekk station
Vollebekk station is a metro stop in Oslo, Norway, located on the city's rapid transit network and serving the surrounding residential area.
- 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f2b08f881909f3d4fab2eda1d67 |
completed | March 31, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf51b7d05c8190b84e02a8796d3422 |
completed | April 3, 2026, 5:35 a.m. |
| NEDg | Description generation | batch_69cf55016d108190b6de72787962564f |
completed | April 3, 2026, 5:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf55940918819088ed8a6ea2f8f460 |
completed | April 3, 2026, 5:52 a.m. |
Created at: March 30, 2026, 6:41 p.m.