Triple
T16123683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arnhem–Nijmegen metropolitan area |
E391208
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Beuningen |
E1003891
|
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: Beuningen | Statement: [Arnhem–Nijmegen metropolitan area, containsMunicipality, Beuningen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beuningen Context triple: [Arnhem–Nijmegen metropolitan area, containsMunicipality, Beuningen]
-
A.
Beuningen
chosen
Beuningen is a municipality and town in the Dutch province of Gelderland, located near the city of Nijmegen in the eastern Netherlands.
-
B.
Beinsdorp
Beinsdorp is a small village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer.
-
C.
Benningen
Benningen is a municipality in the Unterallgäu district of Bavaria in southern Germany.
-
D.
Veeningen
Veeningen is a small village in the Dutch province of Drenthe, located within the municipality of De Wolden.
-
E.
Heijningen
Heijningen is a small village in the Dutch province of North Brabant, located in the municipality of Moerdijk.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020342988190add65c784b8ee179 |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ecc2b4c8190ac9654ac826f198e |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5 a.m.