Triple
T18597150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NorthSide Festival |
E454520
|
entity |
| Predicate | hasMainVenue |
P5921
|
FINISHED |
| Object |
Eskelunden
Eskelunden is a large outdoor area in Aarhus, Denmark, used as the main site for major events and music festivals.
|
E1337665
|
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: Eskelunden | Statement: [NorthSide Festival, hasMainVenue, Eskelunden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eskelunden Context triple: [NorthSide Festival, hasMainVenue, Eskelunden]
-
A.
Emdrup
Emdrup is a district in Copenhagen, Denmark, known for hosting a campus of Aarhus University and various educational and residential facilities.
-
B.
Hornbæk
Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
-
C.
Vollebæk
Vollebæk is a Norwegian surname most notably associated with diplomat and former foreign minister Knut Vollebæk.
-
D.
Birkelunden
Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
-
E.
Søllerød
Søllerød is a locality in Rudersdal Municipality, north of Copenhagen in eastern Denmark, known for its affluent residential areas and scenic natural surroundings.
- 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: Eskelunden Triple: [NorthSide Festival, hasMainVenue, Eskelunden]
Generated description
Eskelunden is a large outdoor area in Aarhus, Denmark, used as the main site for major events and music festivals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eskelunden Target entity description: Eskelunden is a large outdoor area in Aarhus, Denmark, used as the main site for major events and music festivals.
-
A.
Emdrup
Emdrup is a district in Copenhagen, Denmark, known for hosting a campus of Aarhus University and various educational and residential facilities.
-
B.
Hornbæk
Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
-
C.
Vollebæk
Vollebæk is a Norwegian surname most notably associated with diplomat and former foreign minister Knut Vollebæk.
-
D.
Birkelunden
Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
-
E.
Søllerød
Søllerød is a locality in Rudersdal Municipality, north of Copenhagen in eastern Denmark, known for its affluent residential areas and scenic natural surroundings.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5474ce0c08190b440cbe86b6ef7b9 |
completed | April 19, 2026, 9:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05233eb5ec8190acb14c9e66b879ff |
completed | May 14, 2026, 1:19 a.m. |
| NEDg | Description generation | batch_6a0524327ebc8190a613c84cff540d59 |
completed | May 14, 2026, 1:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0527d674fc81908fe4f90ae667802c |
completed | May 14, 2026, 1:39 a.m. |
Created at: April 10, 2026, 11:44 a.m.