Triple
T18184895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funen Painters |
E435385
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object |
Kerteminde
Kerteminde is a coastal town on the Danish island of Funen known for its historic fishing harbor, beaches, and connections to Danish art and culture.
|
E1311397
|
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: Kerteminde | Statement: [Funen Painters, associatedWith, Kerteminde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kerteminde Context triple: [Funen Painters, associatedWith, Kerteminde]
-
A.
Tivissa
Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
-
B.
Kurtalan
Kurtalan is a town and district in Siirt Province in southeastern Turkey, known as the terminus of the historic Kurtalan Express railway line.
-
C.
Kurn
Kurn is a Klingon warrior and the younger brother of Worf in the Star Trek universe.
-
D.
Kerevat
Kerevat is a significant inland town in East New Britain Province of Papua New Guinea, known for its agricultural research station and surrounding cocoa and coconut plantations.
-
E.
Kamen
Kamen is a town in North Rhine-Westphalia, Germany, known as a local industrial and transport hub in the Ruhr region.
- 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: Kerteminde Triple: [Funen Painters, associatedWith, Kerteminde]
Generated description
Kerteminde is a coastal town on the Danish island of Funen known for its historic fishing harbor, beaches, and connections to Danish art and culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kerteminde Target entity description: Kerteminde is a coastal town on the Danish island of Funen known for its historic fishing harbor, beaches, and connections to Danish art and culture.
-
A.
Tivissa
Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
-
B.
Kurtalan
Kurtalan is a town and district in Siirt Province in southeastern Turkey, known as the terminus of the historic Kurtalan Express railway line.
-
C.
Kurn
Kurn is a Klingon warrior and the younger brother of Worf in the Star Trek universe.
-
D.
Kerevat
Kerevat is a significant inland town in East New Britain Province of Papua New Guinea, known for its agricultural research station and surrounding cocoa and coconut plantations.
-
E.
Kamen
Kamen is a town in North Rhine-Westphalia, Germany, known as a local industrial and transport hub in the Ruhr region.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dffdccd881908da772db78b9d081 |
completed | April 19, 2026, 2 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0398032e3081909455845718c73b78 |
completed | May 12, 2026, 9:13 p.m. |
| NEDg | Description generation | batch_6a03990a2bec8190b5d6a472bc9bb3fb |
completed | May 12, 2026, 9:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0399c98a88819090e579324d9423e5 |
completed | May 12, 2026, 9:21 p.m. |
Created at: April 10, 2026, 10:31 a.m.