Triple
T3220385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copenhagen Airport Kastrup |
E67497
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Kastrup
Kastrup is a district in the Tårnby Municipality near Copenhagen, Denmark, best known for hosting the country’s main international airport.
|
E343798
|
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: Kastrup | Statement: [Copenhagen Airport Kastrup, locatedIn, Kastrup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kastrup Context triple: [Copenhagen Airport Kastrup, locatedIn, Kastrup]
-
A.
Hillerød
Hillerød is a Danish town on the island of Zealand, known for the historic Frederiksborg Castle and its role as a regional administrative and cultural center.
-
B.
Ballerup
Ballerup is a suburban municipality near Copenhagen in eastern Denmark, known for its residential areas, business parks, and sports facilities.
-
C.
Rødovre
Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
-
D.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
-
E.
Holbæk
Holbæk is a coastal town and municipality in northwestern Zealand, Denmark, known for its harbor on Holbæk Fjord and role as a regional commercial and cultural 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: Kastrup Triple: [Copenhagen Airport Kastrup, locatedIn, Kastrup]
Generated description
Kastrup is a district in the Tårnby Municipality near Copenhagen, Denmark, best known for hosting the country’s main international airport.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kastrup Target entity description: Kastrup is a district in the Tårnby Municipality near Copenhagen, Denmark, best known for hosting the country’s main international airport.
-
A.
Hillerød
Hillerød is a Danish town on the island of Zealand, known for the historic Frederiksborg Castle and its role as a regional administrative and cultural center.
-
B.
Ballerup
Ballerup is a suburban municipality near Copenhagen in eastern Denmark, known for its residential areas, business parks, and sports facilities.
-
C.
Rødovre
Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
-
D.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
-
E.
Holbæk
Holbæk is a coastal town and municipality in northwestern Zealand, Denmark, known for its harbor on Holbæk Fjord and role as a regional commercial and cultural 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_69ad858b8adc8190ad989712c87a476b |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adae16f20081909d7f3bac016f961d |
completed | March 8, 2026, 5:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e826c50c8190a6e472e7a8862df2 |
completed | March 12, 2026, 4:21 p.m. |
| NEDg | Description generation | batch_69b2e8e42ecc8190b81d1b64f9fba0c1 |
completed | March 12, 2026, 4:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2e954ec18819096f31feb9e985b6a |
completed | March 12, 2026, 4:27 p.m. |
Created at: March 8, 2026, 3:08 p.m.