Triple
T19816765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hvidovre |
E476077
|
entity |
| Predicate | hasSuburb |
P747
|
FINISHED |
| Object |
Avedøre
Avedøre is a suburban district in the Copenhagen metropolitan area of Denmark, known for its large housing estates and diverse population.
|
E1456129
|
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: Avedøre | Statement: [Hvidovre, hasSuburb, Avedøre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avedøre Context triple: [Hvidovre, hasSuburb, Avedøre]
-
A.
Thurø
Thurø is a small Danish island in the Baltic Sea known for its coastal scenery, beaches, and traditional maritime village atmosphere.
-
B.
Rødovre
Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
-
C.
Vollebæk
Vollebæk is a Norwegian surname most notably associated with diplomat and former foreign minister Knut Vollebæk.
-
D.
Hornbæk
Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
-
E.
Vækerø
Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
- 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: Avedøre Triple: [Hvidovre, hasSuburb, Avedøre]
Generated description
Avedøre is a suburban district in the Copenhagen metropolitan area of Denmark, known for its large housing estates and diverse population.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Avedøre Target entity description: Avedøre is a suburban district in the Copenhagen metropolitan area of Denmark, known for its large housing estates and diverse population.
-
A.
Thurø
Thurø is a small Danish island in the Baltic Sea known for its coastal scenery, beaches, and traditional maritime village atmosphere.
-
B.
Rødovre
Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
-
C.
Vollebæk
Vollebæk is a Norwegian surname most notably associated with diplomat and former foreign minister Knut Vollebæk.
-
D.
Hornbæk
Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
-
E.
Vækerø
Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654f9c5b08190987237f5144c3b37 |
completed | April 20, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0918b234588190ac3b70bf4a3220e6 |
completed | May 17, 2026, 1:24 a.m. |
| NEDg | Description generation | batch_6a091971e5308190acdf4a65b1e67118 |
completed | May 17, 2026, 1:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0919f58008819097e05a187ed4b3de |
completed | May 17, 2026, 1:29 a.m. |
Created at: April 10, 2026, 1:50 p.m.