Triple
T14859441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clausen |
E349449
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Alzette valley |
E569988
|
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: Alzette valley | Statement: [Clausen, partOf, Alzette valley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alzette valley Context triple: [Clausen, partOf, Alzette valley]
-
A.
Alzette
chosen
The Alzette is a river in Luxembourg and France that flows through Luxembourg City and ultimately joins the Sauer, making it an important waterway in the region.
-
B.
Rodange
Rodange is a town in southwestern Luxembourg known as an important railway junction near the Belgian and French borders.
-
C.
Aubenas
Aubenas is a historic market town in southern France known for its medieval castle and role as a commercial center of the Ardèche region.
-
D.
Blegny
Blegny is a municipality in eastern Belgium known for its historic coal mining heritage and rural character.
-
E.
Lantheuil
Lantheuil is a small commune in the Calvados department of the Normandy region in northwestern France.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44598e48190b759a05ed2d9ecaf |
completed | April 14, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe650a43bc8190b836fe690d2a3c71 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:54 a.m.