Triple
T11353444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hautes Fagnes |
E268891
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Belgian Eifel |
E297934
|
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: Belgian Eifel | Statement: [Hautes Fagnes, partOf, Belgian Eifel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belgian Eifel Context triple: [Hautes Fagnes, partOf, Belgian Eifel]
-
A.
Eifel (Belgium)
chosen
Eifel (Belgium) is a sparsely populated, hilly region in eastern Belgium known for its forests, nature reserves, and rural landscapes as part of the greater Eifel mountain area.
-
B.
Vaalserberg
Vaalserberg is a hill in the southeastern Netherlands known as the country's highest point and the location of the tripoint where the borders of the Netherlands, Germany, and Belgium meet.
-
C.
Eifel Mountains
The Eifel Mountains are a low mountain range in western Germany and eastern Belgium, known for their volcanic landscapes, dense forests, and picturesque villages.
-
D.
Diedenbergen
Diedenbergen is a district of the town Hofheim am Taunus in the German state of Hesse.
-
E.
Eifel National Park
Eifel National Park is a protected natural area in western Germany known for its ancient beech forests, diverse wildlife, and extensive hiking trails.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea24489081908fbf47fd2e6d709c |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e543a6e97481909dc77a553b217b4d |
completed | April 19, 2026, 9:05 p.m. |
Created at: April 8, 2026, 9:33 p.m.