Triple
T13048503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Condroz |
E327385
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Walhain |
E698488
|
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: Walhain | Statement: [Condroz, containsSettlement, Walhain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walhain Context triple: [Condroz, containsSettlement, Walhain]
-
A.
Walhain
chosen
Walhain is a rural municipality in central Belgium known for its agricultural landscape and historic castle ruins.
-
B.
Kevelaer
Kevelaer is a renowned German pilgrimage town in North Rhine-Westphalia, famous as one of Europe’s most important Marian shrines and a major destination for Catholic pilgrims.
-
C.
Joncreuil
Joncreuil is a small French commune located in the Aube department in the Grand Est region of northeastern France.
-
D.
Audinghen
Audinghen is a small coastal commune in northern France known for its proximity to the scenic Cap Gris-Nez headland on the English Channel.
-
E.
Isselburg
Isselburg is a small town in western North Rhine-Westphalia, Germany, near the Dutch border, known for its rural character and historic buildings.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980b8811c81908577f092e2736610 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e26c1f0081908100cae2cf39ac90 |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 8:57 p.m.