Triple
T15897258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langeraar |
E385489
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Aarlanderveen |
E385491
|
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: Aarlanderveen | Statement: [Langeraar, near, Aarlanderveen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aarlanderveen Context triple: [Langeraar, near, Aarlanderveen]
-
A.
Aarlanderveen
chosen
Aarlanderveen is a village in the Dutch province of South Holland, known for its polder landscape and traditional windmills.
-
B.
Roelofarendsveen
Roelofarendsveen is a town in the Dutch province of South Holland that serves as the administrative center of the municipality of Kaag en Braassem.
-
C.
Griendtsveen
Griendtsveen is a small Dutch village known for its historic peat-extraction landscape and canals in the southeastern Netherlands.
-
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.
Veenendaal
Veenendaal is a Dutch town and municipality in the central Netherlands, known for its location between Utrecht and the Veluwe and its mix of residential, commercial, and light industrial areas.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15639c9748190b1115f74cbd61330 |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5a1b1548190a8579cebf9e71121 |
completed | May 9, 2026, 10:30 p.m. |
Created at: April 10, 2026, 4:51 a.m.