Triple
T6155306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drimmelen |
E137305
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Wagenberg
Wagenberg is a village in the Dutch province of North Brabant, located within the municipality of Drimmelen.
|
E572769
|
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: Wagenberg | Statement: [Drimmelen, hasPart, Wagenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wagenberg Context triple: [Drimmelen, hasPart, Wagenberg]
-
A.
Wilseder Berg
Wilseder Berg is a prominent hill and popular viewpoint in northern Germany, known for its scenic heathland landscapes within the Lüneburg Heath region.
-
B.
Mount Klabat
Mount Klabat is a stratovolcano and the highest peak in North Sulawesi, Indonesia, known for its crater lake and popular hiking routes.
-
C.
Monte Renoso
Monte Renoso is a prominent mountain in southern Corsica, France, known for its rugged terrain and scenic alpine landscapes.
-
D.
Hoche
Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
-
E.
Monteiasi
Monteiasi is a small town and comune in the Apulia region of southern Italy, known for its traditional rural character and proximity to the city of Taranto.
- 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: Wagenberg Triple: [Drimmelen, hasPart, Wagenberg]
Generated description
Wagenberg is a village in the Dutch province of North Brabant, located within the municipality of Drimmelen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wagenberg Target entity description: Wagenberg is a village in the Dutch province of North Brabant, located within the municipality of Drimmelen.
-
A.
Wilseder Berg
Wilseder Berg is a prominent hill and popular viewpoint in northern Germany, known for its scenic heathland landscapes within the Lüneburg Heath region.
-
B.
Mount Klabat
Mount Klabat is a stratovolcano and the highest peak in North Sulawesi, Indonesia, known for its crater lake and popular hiking routes.
-
C.
Monte Renoso
Monte Renoso is a prominent mountain in southern Corsica, France, known for its rugged terrain and scenic alpine landscapes.
-
D.
Hoche
Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
-
E.
Monteiasi
Monteiasi is a small town and comune in the Apulia region of southern Italy, known for its traditional rural character and proximity to the city of Taranto.
- 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_69c008a45d008190832a9e19f5d63406 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d01ddb0819085b5f5338b86a25d |
completed | March 22, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1418195d8819092743f323430b9a8 |
completed | March 23, 2026, 1:34 p.m. |
| NEDg | Description generation | batch_69c144696f80819092131e86a3bb3b63 |
completed | March 23, 2026, 1:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c144c523c48190a709342dc031d2b8 |
completed | March 23, 2026, 1:48 p.m. |
Created at: March 22, 2026, 4:17 p.m.