Triple
T13467803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Beveland |
E311547
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Geersdijk
Geersdijk is a small village located on the island of North Beveland in the Dutch province of Zeeland.
|
E1055447
|
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: Geersdijk | Statement: [North Beveland, containsSettlement, Geersdijk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geersdijk Context triple: [North Beveland, containsSettlement, Geersdijk]
-
A.
Nieuwendijk
Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
-
B.
Grijpskerke
Grijpskerke is a village in the Dutch province of Zeeland, located on the former island of Walcheren.
-
C.
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.
-
D.
Vollenhove
Vollenhove is a historic town in the Dutch province of Overijssel, known for its former status as a regional administrative and noble center with several notable estates and churches.
-
E.
Bovenkerk
Bovenkerk is a prominent historic church in the Dutch city of Kampen, known for its Gothic architecture and significant cultural and religious heritage.
- 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: Geersdijk Triple: [North Beveland, containsSettlement, Geersdijk]
Generated description
Geersdijk is a small village located on the island of North Beveland in the Dutch province of Zeeland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Geersdijk Target entity description: Geersdijk is a small village located on the island of North Beveland in the Dutch province of Zeeland.
-
A.
Nieuwendijk
Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
-
B.
Grijpskerke
Grijpskerke is a village in the Dutch province of Zeeland, located on the former island of Walcheren.
-
C.
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.
-
D.
Vollenhove
Vollenhove is a historic town in the Dutch province of Overijssel, known for its former status as a regional administrative and noble center with several notable estates and churches.
-
E.
Bovenkerk
Bovenkerk is a prominent historic church in the Dutch city of Kampen, known for its Gothic architecture and significant cultural and religious heritage.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf101a1081909f2aba6da47baacc |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7942424bc8190af98462f6b7a93a4 |
completed | May 3, 2026, 6:29 p.m. |
| NEDg | Description generation | batch_69f79523bf608190addeca563bea132e |
completed | May 3, 2026, 6:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7965cc9f88190acbf232615a9e87b |
completed | May 3, 2026, 6:39 p.m. |
Created at: April 9, 2026, 9:42 p.m.