Triple
T18597340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aarhus Letbane |
E454525
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object |
Aarhus H
Aarhus H is the main railway station in Aarhus, Denmark, serving as a central hub for regional, national, and light rail services.
|
E1343088
|
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: Aarhus H | Statement: [Aarhus Letbane, terminus, Aarhus H]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aarhus H Context triple: [Aarhus Letbane, terminus, Aarhus H]
-
A.
Aarhus V
Aarhus V is a district in the western part of Aarhus, Denmark, known for its residential areas and cultural diversity.
-
B.
Aarhus
Aarhus is Denmark’s second-largest city, a major cultural and economic center on the Jutland peninsula known for its universities, vibrant arts scene, and historic harbor.
-
C.
Aarhus C
Aarhus C is the central district of Aarhus, Denmark, known as the city’s historic and cultural core with major attractions, shopping streets, and urban life.
-
D.
København H
København H is Copenhagen’s central railway station and the main hub for regional, national, and S-train services in Denmark’s capital.
-
E.
Herning
Herning is a Danish city in the Central Jutland region known for its trade fairs, conference facilities, and vibrant cultural and sports events.
- 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: Aarhus H Triple: [Aarhus Letbane, terminus, Aarhus H]
Generated description
Aarhus H is the main railway station in Aarhus, Denmark, serving as a central hub for regional, national, and light rail services.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aarhus H Target entity description: Aarhus H is the main railway station in Aarhus, Denmark, serving as a central hub for regional, national, and light rail services.
-
A.
Aarhus V
Aarhus V is a district in the western part of Aarhus, Denmark, known for its residential areas and cultural diversity.
-
B.
Aarhus
Aarhus is Denmark’s second-largest city, a major cultural and economic center on the Jutland peninsula known for its universities, vibrant arts scene, and historic harbor.
-
C.
Aarhus C
Aarhus C is the central district of Aarhus, Denmark, known as the city’s historic and cultural core with major attractions, shopping streets, and urban life.
-
D.
København H
København H is Copenhagen’s central railway station and the main hub for regional, national, and S-train services in Denmark’s capital.
-
E.
Herning
Herning is a Danish city in the Central Jutland region known for its trade fairs, conference facilities, and vibrant cultural and sports events.
- 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_6a054702a4008190afe8744520d4dfcb |
completed | May 14, 2026, 3:52 a.m. |
| NEDg | Description generation | batch_6a054a15410c819090fbed16c2331ead |
completed | May 14, 2026, 4:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a054a8c26848190b24073356b0cdf2c |
completed | May 14, 2026, 4:07 a.m. |
Created at: April 10, 2026, 11:44 a.m.