Triple
T4169565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ede |
E84526
|
entity |
| Predicate | containsVillage |
P4011
|
FINISHED |
| Object |
Bennekom
Bennekom is a village in the Dutch province of Gelderland, known for its green surroundings and location between the cities of Ede and Wageningen.
|
E843817
|
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: Bennekom | Statement: [Ede, containsVillage, Bennekom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bennekom Context triple: [Ede, containsVillage, Bennekom]
-
A.
Bloemendaal
Bloemendaal is a coastal municipality in North Holland, Netherlands, known for its beaches, dunes, and affluent residential areas.
-
B.
Nieuwendijk
Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
-
C.
Schoonhoven
Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
-
D.
Bezuidenhout
Bezuidenhout is a neighborhood in The Hague, Netherlands, known for its residential character and proximity to major government and business districts.
-
E.
Groesbeek
Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
- 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: Bennekom Triple: [Ede, containsVillage, Bennekom]
Generated description
Bennekom is a village in the Dutch province of Gelderland, known for its green surroundings and location between the cities of Ede and Wageningen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bennekom Target entity description: Bennekom is a village in the Dutch province of Gelderland, known for its green surroundings and location between the cities of Ede and Wageningen.
-
A.
Bloemendaal
Bloemendaal is a coastal municipality in North Holland, Netherlands, known for its beaches, dunes, and affluent residential areas.
-
B.
Nieuwendijk
Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
-
C.
Schoonhoven
Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
-
D.
Bezuidenhout
Bezuidenhout is a neighborhood in The Hague, Netherlands, known for its residential character and proximity to major government and business districts.
-
E.
Groesbeek
Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
- 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02c730b081908b19e6a4aea1549b |
completed | March 9, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e4b5781c8190b33035b81dd74260 |
completed | April 5, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69d2e6f0aa988190aa9a866afcc2a1a2 |
completed | April 5, 2026, 10:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d2e78384f48190abb7bdd7fcadcd9a |
completed | April 5, 2026, 10:51 p.m. |
Created at: March 9, 2026, 3:44 p.m.