Triple
T17531025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierroz River |
E426930
|
entity |
| Predicate | mouth |
P407
|
FINISHED |
| Object | Lake Bourget |
—
|
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: Lake Bourget | Statement: [Sierroz River, mouth, Lake Bourget]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Bourget Context triple: [Sierroz River, mouth, Lake Bourget]
-
A.
Lake Bourget
Lake Bourget is a large glacial lake in eastern France, renowned for its scenic Alpine setting, biodiversity, and popularity as a destination for boating and outdoor recreation.
-
B.
Dayet Aoua Lake
Dayet Aoua Lake is a scenic freshwater lake in Morocco’s Middle Atlas region, popular for its natural beauty, birdlife, and outdoor recreation.
-
C.
Lake of Tunis
Lake of Tunis is a coastal lagoon near the city of Tunis in Tunisia, historically significant as a natural harbor and ecological wetland area.
-
D.
Lac du Bourget
chosen
Lac du Bourget is a large glacial lake in the Savoie region of southeastern France, known for its scenic Alpine setting and popular recreational activities.
-
E.
Lac Pavin
Lac Pavin is a deep, nearly circular volcanic crater lake in France’s Auvergne region, renowned for its meromictic waters and scenic setting.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e453688950819098162d853cd2674e |
completed | April 19, 2026, 4 a.m. |
Created at: April 10, 2026, 5:49 a.m.