Triple
T5952387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aa en Hunze |
E132430
|
entity |
| Predicate | hasAdministrativeCenter |
P1474
|
FINISHED |
| Object |
Gieten
Gieten is a village in the Dutch province of Drenthe that serves as the main administrative and service hub for the surrounding rural municipality.
|
E557914
|
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: Gieten | Statement: [Aa en Hunze, hasAdministrativeCenter, Gieten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gieten Context triple: [Aa en Hunze, hasAdministrativeCenter, Gieten]
-
A.
Geldern
Geldern is a historic town in western Germany, notable as the namesake and former center of the medieval Duchy of Guelders.
-
B.
Winschoten
Winschoten is a town in the northeast of the Netherlands known historically as a regional trade center and for its traditional windmills and Jewish heritage.
-
C.
Rijkevoort
Rijkevoort is a village in the Dutch province of North Brabant, known for its rural character and location near the German border.
-
D.
Uithoorn
Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
-
E.
Akkerman
Akkerman, historically known as Cetatea Albă and now called Bilhorod-Dnistrovskyi, is an ancient fortress town in southwestern Ukraine near the Black Sea.
- 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: Gieten Triple: [Aa en Hunze, hasAdministrativeCenter, Gieten]
Generated description
Gieten is a village in the Dutch province of Drenthe that serves as the main administrative and service hub for the surrounding rural municipality.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gieten Target entity description: Gieten is a village in the Dutch province of Drenthe that serves as the main administrative and service hub for the surrounding rural municipality.
-
A.
Geldern
Geldern is a historic town in western Germany, notable as the namesake and former center of the medieval Duchy of Guelders.
-
B.
Winschoten
Winschoten is a town in the northeast of the Netherlands known historically as a regional trade center and for its traditional windmills and Jewish heritage.
-
C.
Rijkevoort
Rijkevoort is a village in the Dutch province of North Brabant, known for its rural character and location near the German border.
-
D.
Uithoorn
Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
-
E.
Akkerman
Akkerman, historically known as Cetatea Albă and now called Bilhorod-Dnistrovskyi, is an ancient fortress town in southwestern Ukraine near the Black Sea.
- 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_69c0086b05cc8190a8f36a96927a525c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03983b8848190afaa37f35c95bad6 |
completed | March 22, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e3d1801c819093dc43dc5a525796 |
completed | March 23, 2026, 6:55 a.m. |
| NEDg | Description generation | batch_69c0e781af588190a8f5572a03b24822 |
completed | March 23, 2026, 7:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0e7f767f8819086026b95c4534733 |
completed | March 23, 2026, 7:12 a.m. |
Created at: March 22, 2026, 4:02 p.m.