Triple
T20892377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nisramont Dam |
E514438
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object | Houffalize |
—
|
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: Houffalize | Statement: [Nisramont Dam, nearbySettlement, Houffalize]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Houffalize Context triple: [Nisramont Dam, nearbySettlement, Houffalize]
-
A.
Houffalize
chosen
Houffalize is a small town in the Belgian Ardennes known for its World War II history, outdoor tourism, and scenic natural surroundings.
-
B.
Gochenée
Gochenée is a small village in Wallonia, Belgium, known primarily as the birthplace of the 19th-century architect Alphonse Balat.
-
C.
Beaufays
Beaufays is a village in the municipality of Chaudfontaine in the province of Liège, Belgium.
-
D.
Donges
Donges is a commune in western France’s Loire-Atlantique department, known for its major oil refinery and industrial port facilities along the Loire River.
-
E.
Boechout
Boechout is a municipality in the Belgian province of Antwerp, known for its suburban character and proximity to the city of Antwerp.
- 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_69e0b4f7ebe48190952a85547a0f31a1 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6d05f0bec8190a296db546bd34114 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 12:46 p.m.