Triple
T10690426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murtensee |
E251994
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object | Avenches |
E515695
|
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: Avenches | Statement: [Murtensee, hasNearbyTown, Avenches]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avenches Context triple: [Murtensee, hasNearbyTown, Avenches]
-
A.
Avenches
chosen
Avenches is a historic town in western Switzerland, known for its well-preserved Roman ruins and amphitheater.
-
B.
Léognan
Léognan is a renowned wine-producing commune in southwestern France, celebrated for its prestigious red and white Bordeaux wines.
-
C.
Embrun
Embrun is a historic town in southeastern France’s Hautes-Alpes department, known for its picturesque setting in the Alps and proximity to the Lac de Serre-Ponçon.
-
D.
Embrun
Embrun is a rapidly growing Franco-Ontarian community in eastern Ontario, known for its bilingual character and proximity to Ottawa.
-
E.
Chevenez
Chevenez is a village in the Ajoie region of the canton of Jura in northwestern Switzerland.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd1c0f0081908a6869ee756ec789 |
completed | April 9, 2026, 1:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2161018408190bcb64efba0974f8c |
completed | April 17, 2026, 11:14 a.m. |
Created at: April 8, 2026, 9:11 p.m.