Triple
T3670797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christiaan Eijkman |
E77873
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Nijkerk
Nijkerk is a historic town and municipality in the Dutch province of Gelderland in the central Netherlands.
|
E763791
|
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: Nijkerk | Statement: [Christiaan Eijkman, placeOfBirth, Nijkerk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nijkerk Context triple: [Christiaan Eijkman, placeOfBirth, Nijkerk]
-
A.
Nijverdal
Nijverdal is a town in the Dutch province of Overijssel known as a gateway to the Sallandse Heuvelrug National Park and its surrounding natural landscapes.
-
B.
Nieuwendijk
Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
-
C.
Cuijk
Cuijk is a historic town in the Dutch province of North Brabant, known for its Roman-era heritage and location along the River Meuse.
-
D.
Papendrecht
Papendrecht is a Dutch town situated on the river Merwede in the province of South Holland, known for its residential character and proximity to the city of Dordrecht.
-
E.
Nuenen
Nuenen is a village in the southern Netherlands, known for its association with both the painter Vincent van Gogh and computer scientist Edsger W. Dijkstra.
- 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: Nijkerk Triple: [Christiaan Eijkman, placeOfBirth, Nijkerk]
Generated description
Nijkerk is a historic town and municipality in the Dutch province of Gelderland in the central Netherlands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nijkerk Target entity description: Nijkerk is a historic town and municipality in the Dutch province of Gelderland in the central Netherlands.
-
A.
Nijverdal
Nijverdal is a town in the Dutch province of Overijssel known as a gateway to the Sallandse Heuvelrug National Park and its surrounding natural landscapes.
-
B.
Nieuwendijk
Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
-
C.
Cuijk
Cuijk is a historic town in the Dutch province of North Brabant, known for its Roman-era heritage and location along the River Meuse.
-
D.
Papendrecht
Papendrecht is a Dutch town situated on the river Merwede in the province of South Holland, known for its residential character and proximity to the city of Dordrecht.
-
E.
Nuenen
Nuenen is a village in the southern Netherlands, known for its association with both the painter Vincent van Gogh and computer scientist Edsger W. Dijkstra.
- 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc42c96648190abbd5d23b25d6a6b |
completed | March 8, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfaae99194819095cf9b74267956a4 |
completed | April 3, 2026, 11:56 a.m. |
| NEDg | Description generation | batch_69cfac76d0f8819090c2bff520db52f4 |
completed | April 3, 2026, 12:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfad04e514819084bf30b8f026c031 |
completed | April 3, 2026, 12:05 p.m. |
Created at: March 8, 2026, 3:25 p.m.