Triple
T1067043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limburg (Netherlands) |
E23233
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Weert
Weert is a municipality and city in the southeastern Netherlands known as a regional center in the province of Limburg.
|
E463111
|
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: Weert | Statement: [Limburg (Netherlands), containsCity, Weert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weert Context triple: [Limburg (Netherlands), containsCity, Weert]
-
A.
Winterswijk
Winterswijk is a town in the eastern Netherlands known for its rural landscape, textile-industry history, and location near the German border.
-
B.
Uithoorn
Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
-
C.
Scharendijke
Scharendijke is a village in the Dutch province of Zeeland, known as a popular base for water sports and diving in the Grevelingen and North Sea area.
-
D.
Steenwijk
Steenwijk is a historic town in the Dutch province of Overijssel, known for its medieval center and role as a regional hub in the north of the province.
-
E.
Zwijndrecht
Zwijndrecht is a Dutch town and municipality located in the western Netherlands, known for its position along the rivers near the city of Dordrecht.
- 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: Weert Triple: [Limburg (Netherlands), containsCity, Weert]
Generated description
Weert is a municipality and city in the southeastern Netherlands known as a regional center in the province of Limburg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weert Target entity description: Weert is a municipality and city in the southeastern Netherlands known as a regional center in the province of Limburg.
-
A.
Winterswijk
Winterswijk is a town in the eastern Netherlands known for its rural landscape, textile-industry history, and location near the German border.
-
B.
Uithoorn
Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
-
C.
Scharendijke
Scharendijke is a village in the Dutch province of Zeeland, known as a popular base for water sports and diving in the Grevelingen and North Sea area.
-
D.
Steenwijk
Steenwijk is a historic town in the Dutch province of Overijssel, known for its medieval center and role as a regional hub in the north of the province.
-
E.
Zwijndrecht
Zwijndrecht is a Dutch town and municipality located in the western Netherlands, known for its position along the rivers near the city of Dordrecht.
- 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_69a493ee1f908190992b5f0d1b04459b |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b911f06881908659cb85ba1e05e0 |
completed | March 1, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be0ffd52188190addb5fa69c45e9d7 |
completed | March 21, 2026, 3:26 a.m. |
| NEDg | Description generation | batch_69be10cce8d0819093c9f1c721142e48 |
completed | March 21, 2026, 3:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be119987bc8190b0b0f75a2c07a60c |
completed | March 21, 2026, 3:33 a.m. |
Created at: March 1, 2026, 7:42 p.m.