Triple
T11506960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Bourget-du-Lac |
E272808
|
entity |
| Predicate | hasLakeShoreLength |
P76887
|
FINISHED |
| Object | several kilometres on Lac du Bourget |
—
|
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: several kilometres on Lac du Bourget | Statement: [Le Bourget-du-Lac, hasLakeShoreLength, several kilometres on Lac du Bourget]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakeShoreLength Context triple: [Le Bourget-du-Lac, hasLakeShoreLength, several kilometres on Lac du Bourget]
-
A.
hasLakeshore
Indicates that one entity is located along or directly borders the shore of a lake associated with another entity.
-
B.
hasShoreLengthUnit
Indicates the unit of measurement used to express the length of a shore or coastline.
-
C.
hasShoreLengthOn
chosen
Indicates that an entity has a specified length of shoreline along or bordering another geographic feature (such as a body of water or coast).
-
D.
hasPierLength
Indicates that one entity (typically a pier or similar structure) has a specified length measurement.
-
E.
shorelineLength
Indicates the total measured extent of a land area’s boundary where it meets a body of water.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d86db43a648190be859bec2fe9f43b |
completed | April 10, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.