Triple
T22155030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalfsen |
E547512
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Hoonhorst
Hoonhorst is a small village in the Dutch province of Overijssel, known for its rural character and historic church.
|
E1524849
|
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: Hoonhorst | Statement: [Dalfsen, hasSettlement, Hoonhorst]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoonhorst Context triple: [Dalfsen, hasSettlement, Hoonhorst]
-
A.
De Horst
De Horst is a village in the Dutch province of Gelderland, known as part of the municipality of Berg en Dal near the city of Nijmegen.
-
B.
Brinkhorst
Brinkhorst is the Dutch family name of Princess Laurentien of the Netherlands, associated with a prominent political and aristocratic lineage.
-
C.
Struycken
Struycken is a Dutch surname most notably borne by actor Carel Struycken, known for his distinctive tall stature and roles in film and television.
-
D.
Bronkhorst
Bronkhorst is a small historic town in the Netherlands often regarded as one of the country’s smallest and known for its well-preserved medieval character.
-
E.
Hudde
Hudde is a Dutch surname most notably associated with Johannes Hudde, a 17th-century mathematician and mayor of Amsterdam known for his contributions to algebra and optics.
- 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: Hoonhorst Triple: [Dalfsen, hasSettlement, Hoonhorst]
Generated description
Hoonhorst is a small village in the Dutch province of Overijssel, known for its rural character and historic church.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hoonhorst Target entity description: Hoonhorst is a small village in the Dutch province of Overijssel, known for its rural character and historic church.
-
A.
De Horst
De Horst is a village in the Dutch province of Gelderland, known as part of the municipality of Berg en Dal near the city of Nijmegen.
-
B.
Brinkhorst
Brinkhorst is the Dutch family name of Princess Laurentien of the Netherlands, associated with a prominent political and aristocratic lineage.
-
C.
Struycken
Struycken is a Dutch surname most notably borne by actor Carel Struycken, known for his distinctive tall stature and roles in film and television.
-
D.
Bronkhorst
Bronkhorst is a small historic town in the Netherlands often regarded as one of the country’s smallest and known for its well-preserved medieval character.
-
E.
Hudde
Hudde is a Dutch surname most notably associated with Johannes Hudde, a 17th-century mathematician and mayor of Amsterdam known for his contributions to algebra and optics.
- 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_69e11e3b52088190ad5df386d01eb2fb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129f7d034819092ecf9682e549c9a |
completed | April 28, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0aa602503881908fafd095f40e6681 |
completed | May 18, 2026, 5:39 a.m. |
| NEDg | Description generation | batch_6a0aa6b04798819088ab3ed8c3fe53af |
completed | May 18, 2026, 5:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0aa72467d4819093f84573de7c8da2 |
completed | May 18, 2026, 5:44 a.m. |
Created at: April 16, 2026, 8:33 p.m.