Triple
T6925798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texel |
E160304
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
De Koog
De Koog is a coastal village and popular seaside resort on the Dutch Wadden Island of Texel, known for its beaches, dunes, and tourism.
|
E629829
|
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: De Koog | Statement: [Texel, containsSettlement, De Koog]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: De Koog Context triple: [Texel, containsSettlement, De Koog]
-
A.
Wessum
Wessum is a village and district within the town of Ahaus in the state of North Rhine-Westphalia, Germany.
-
B.
Veendam
Veendam is a town and municipality in the province of Groningen in the northeastern Netherlands, historically known for peat extraction and later for its industrial development.
-
C.
Eemshaven
Eemshaven is a major seaport and energy hub in the north of the Netherlands, known for its power plants, data centers, and offshore wind connections.
-
D.
Vlieland
Vlieland is a sparsely populated Dutch Wadden Sea island known for its wide beaches, dunes, and car-free, nature-focused tourism.
-
E.
Spiekeroog
Spiekeroog is a car-free German North Sea island known for its tranquil beaches, dunes, and traditional Frisian village atmosphere.
- 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: De Koog Triple: [Texel, containsSettlement, De Koog]
Generated description
De Koog is a coastal village and popular seaside resort on the Dutch Wadden Island of Texel, known for its beaches, dunes, and tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: De Koog Target entity description: De Koog is a coastal village and popular seaside resort on the Dutch Wadden Island of Texel, known for its beaches, dunes, and tourism.
-
A.
Wessum
Wessum is a village and district within the town of Ahaus in the state of North Rhine-Westphalia, Germany.
-
B.
Veendam
Veendam is a town and municipality in the province of Groningen in the northeastern Netherlands, historically known for peat extraction and later for its industrial development.
-
C.
Eemshaven
Eemshaven is a major seaport and energy hub in the north of the Netherlands, known for its power plants, data centers, and offshore wind connections.
-
D.
Vlieland
Vlieland is a sparsely populated Dutch Wadden Sea island known for its wide beaches, dunes, and car-free, nature-focused tourism.
-
E.
Spiekeroog
Spiekeroog is a car-free German North Sea island known for its tranquil beaches, dunes, and traditional Frisian village atmosphere.
- 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_69c6884d350081908d8a970e4d40ad78 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da1aa9c48190b63a04be2ed9e266 |
completed | March 27, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7513fddd88190b99c4b7e3364d218 |
completed | March 28, 2026, 3:55 a.m. |
| NEDg | Description generation | batch_69c7523737e48190b2ad3e7bea02878d |
completed | March 28, 2026, 3:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c752eb3e1c8190bad35727e573c41f |
completed | March 28, 2026, 4:02 a.m. |
Created at: March 27, 2026, 2:27 p.m.