Triple
T18797020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vendsyssel |
E459660
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object |
Sæby
Sæby is a coastal town in northern Jutland, Denmark, known for its historic town center, marina, and sandy beaches along the Kattegat.
|
E1362135
|
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: Sæby | Statement: [Vendsyssel, hasMajorTown, Sæby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sæby Context triple: [Vendsyssel, hasMajorTown, Sæby]
-
A.
Skjern
Skjern is a town in western Jutland, Denmark, known for its location near the Skjern River and its surrounding agricultural landscape.
-
B.
Hellebæk
Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
-
C.
Sakskøbing
Sakskøbing is a small town on the Danish island of Lolland, known for its historic church, harbor, and surrounding agricultural landscape.
-
D.
Rødby
Rødby is a small town on the Danish island of Lolland, known historically as a ferry port linking Denmark and Germany across the Baltic Sea.
-
E.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
- 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: Sæby Triple: [Vendsyssel, hasMajorTown, Sæby]
Generated description
Sæby is a coastal town in northern Jutland, Denmark, known for its historic town center, marina, and sandy beaches along the Kattegat.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sæby Target entity description: Sæby is a coastal town in northern Jutland, Denmark, known for its historic town center, marina, and sandy beaches along the Kattegat.
-
A.
Skjern
Skjern is a town in western Jutland, Denmark, known for its location near the Skjern River and its surrounding agricultural landscape.
-
B.
Hellebæk
Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
-
C.
Sakskøbing
Sakskøbing is a small town on the Danish island of Lolland, known for its historic church, harbor, and surrounding agricultural landscape.
-
D.
Rødby
Rødby is a small town on the Danish island of Lolland, known historically as a ferry port linking Denmark and Germany across the Baltic Sea.
-
E.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a020821881909749f6a1c6cd195b |
completed | April 20, 2026, 3:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a06f896e9b48190a1117018dcd3add3 |
completed | May 15, 2026, 10:42 a.m. |
| NEDg | Description generation | batch_6a06f948932c8190a4ce08178c00b251 |
completed | May 15, 2026, 10:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a06f9e1fb708190958c64fd38d32d04 |
completed | May 15, 2026, 10:48 a.m. |
Created at: April 10, 2026, 11:53 a.m.