Triple
T1270890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lek |
E15705
|
entity |
| Predicate | flowsNear |
P350
|
FINISHED |
| Object |
Schoonhoven
Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
|
E527517
|
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: Schoonhoven | Statement: [Lek, flowsNear, Schoonhoven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schoonhoven Context triple: [Lek, flowsNear, Schoonhoven]
-
A.
Veldhoven
Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
-
B.
Roosendaal
Roosendaal is a city in the southern Netherlands known as a regional center for commerce and transport near the Belgian border.
-
C.
Barendrecht
Barendrecht is a suburban town in the western Netherlands, located just south of Rotterdam and known for its residential character and logistics industry.
-
D.
Rijkevoort
Rijkevoort is a village in the Dutch province of North Brabant, known for its rural character and location near the German border.
-
E.
Bloemendaal
Bloemendaal is a coastal municipality in North Holland, Netherlands, known for its beaches, dunes, and affluent residential areas.
- 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: Schoonhoven Triple: [Lek, flowsNear, Schoonhoven]
Generated description
Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schoonhoven Target entity description: Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
-
A.
Veldhoven
Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
-
B.
Roosendaal
Roosendaal is a city in the southern Netherlands known as a regional center for commerce and transport near the Belgian border.
-
C.
Barendrecht
Barendrecht is a suburban town in the western Netherlands, located just south of Rotterdam and known for its residential character and logistics industry.
-
D.
Rijkevoort
Rijkevoort is a village in the Dutch province of North Brabant, known for its rural character and location near the German border.
-
E.
Bloemendaal
Bloemendaal is a coastal municipality in North Holland, Netherlands, known for its beaches, dunes, and affluent residential areas.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c06ae7b88190a1e0b5232d84a7b1 |
completed | March 1, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfeceaa8b08190943f7b4291c8bf28 |
completed | March 22, 2026, 1:21 p.m. |
| NEDg | Description generation | batch_69bfedbc80e48190a501370c4547bf6d |
completed | March 22, 2026, 1:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bfee06558881909dd4304f0ca880a2 |
completed | March 22, 2026, 1:26 p.m. |
Created at: March 1, 2026, 7:50 p.m.