Triple
T21557062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halver |
E531919
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Kierspe |
—
|
NE NERFINISHED |
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: Kierspe | Statement: [Halver, locatedNear, Kierspe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kierspe Context triple: [Halver, locatedNear, Kierspe]
-
A.
Kierspe
chosen
Kierspe is a small town in the Märkischer Kreis district of North Rhine-Westphalia, western Germany, known for its rural character and location in the Sauerland region.
-
B.
Yerseke
Yerseke is a Dutch village in the province of Zeeland, best known for its mussel and oyster farming along the Eastern Scheldt.
-
C.
Bergeijk
Bergeijk is a municipality and village in the southern Netherlands, located in the province of North Brabant near the Belgian border.
-
D.
Nunspeet
Nunspeet is a Dutch town and municipality on the Veluwe known for its forests, heathlands, and role as a popular nature and holiday destination.
-
E.
Heiligenhaus
Heiligenhaus is a small town in North Rhine-Westphalia, western Germany, known for its manufacturing industry and location between Düsseldorf and Essen.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c460232c81908de2c3819d17c00e |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eed2e04b048190ac3a9913094b4625 |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 16, 2026, 6:29 p.m.