Triple
T10220633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siddeburen |
E242566
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | Siddebuuren |
E242566
|
NE FINISHED |
How this triple was built (2 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: Siddebuuren | Statement: [Siddeburen, nativeName, Siddebuuren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siddebuuren Context triple: [Siddeburen, nativeName, Siddebuuren]
-
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.
Siddeburen
chosen
Siddeburen is a village in the Dutch province of Groningen, located within the municipality of Eemsdelta.
-
C.
Kloosterburen
Kloosterburen is a small village in the Dutch province of Groningen, known for its historic churches and rural character.
-
D.
Beinsdorp
Beinsdorp is a small village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer.
-
E.
Groesbeek
Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa72b258819097d8d50a714e19dc |
completed | April 6, 2026, 12:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71c8511008190a30008ed32a983d1 |
completed | April 9, 2026, 3:27 a.m. |
Created at: April 6, 2026, 11:09 a.m.