Triple
T17686902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gribskov Line |
E440915
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object |
Græsted
Græsted is a small town in North Zealand, Denmark, known for its rural character and location along the Gribskov railway line.
|
E1296230
|
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: Græsted | Statement: [Gribskov Line, connects, Græsted]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Græsted Context triple: [Gribskov Line, connects, Græsted]
-
A.
Hvide Sande
Hvide Sande is a Danish coastal town and fishing port situated on the narrow isthmus between the North Sea and Ringkøbing Fjord, known for its maritime industry and tourism.
-
B.
Blangsted
Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
-
C.
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.
-
D.
Skælskør
Skælskør is a small coastal town in western Zealand, Denmark, known for its historic harbor, scenic fjord, and traditional Danish architecture.
-
E.
Ginnerup
Ginnerup is a small village in Denmark best known as the birthplace of former Danish Prime Minister and NATO Secretary General Anders Fogh Rasmussen.
- 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: Græsted Triple: [Gribskov Line, connects, Græsted]
Generated description
Græsted is a small town in North Zealand, Denmark, known for its rural character and location along the Gribskov railway line.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Græsted Target entity description: Græsted is a small town in North Zealand, Denmark, known for its rural character and location along the Gribskov railway line.
-
A.
Hvide Sande
Hvide Sande is a Danish coastal town and fishing port situated on the narrow isthmus between the North Sea and Ringkøbing Fjord, known for its maritime industry and tourism.
-
B.
Blangsted
Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
-
C.
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.
-
D.
Skælskør
Skælskør is a small coastal town in western Zealand, Denmark, known for its historic harbor, scenic fjord, and traditional Danish architecture.
-
E.
Ginnerup
Ginnerup is a small village in Denmark best known as the birthplace of former Danish Prime Minister and NATO Secretary General Anders Fogh Rasmussen.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e470488c4081909b747313ef97b69c |
completed | April 19, 2026, 6:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03211a2a888190af5ac374902a6743 |
completed | May 12, 2026, 12:46 p.m. |
| NEDg | Description generation | batch_6a0321e2ce7c81909f24975b71f73621 |
completed | May 12, 2026, 12:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a032255c76c81909ab534ae3e8adddc |
completed | May 12, 2026, 12:51 p.m. |
Created at: April 10, 2026, 10:03 a.m.