Triple
T4699196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lac de Serre-Ponçon |
E104223
|
entity |
| Predicate | shoreFeatures |
P6651
|
FINISHED |
| Object | beaches |
—
|
LITERAL 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: beaches | Statement: [Lac de Serre-Ponçon, shoreFeatures, beaches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shoreFeatures Context triple: [Lac de Serre-Ponçon, shoreFeatures, beaches]
-
A.
coastlineFeature
Indicates that a geographic entity is a specific type of feature located along or forming part of a coastline.
-
B.
shoreType
Indicates the kind or classification of a shoreline associated with a body of water or coastal area.
-
C.
containsCoastalFeature
Indicates that one entity geographically includes or encompasses a coastal feature (such as a beach, cliff, bay, or shoreline) within its area or boundaries.
-
D.
shorelineIncludes
Indicates that a shoreline spatially contains or encompasses a specified coastal feature or segment.
-
E.
hasShoreFeature
chosen
Indicates that a shore or coastline possesses a specific physical or environmental feature.
- F. None of above.
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_69bd43e9b88481908582103dcadff3d9 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650ad0f88190844bfcb46b3071c2 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd621ba7448190a53ab1e2897acf71 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:17 p.m.