Triple
T34274942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beuvron-en-Auge |
E879424
|
entity |
| Predicate | hasNearbySeasideResort |
P181693
|
FINISHED |
| Object | Cabourg |
—
|
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: Cabourg | Statement: [Beuvron-en-Auge, hasNearbySeasideResort, Cabourg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbySeasideResort Context triple: [Beuvron-en-Auge, hasNearbySeasideResort, Cabourg]
-
A.
isSeasideResort
Indicates that a place functions as a resort located by the sea, typically offering coastal leisure and tourism activities.
-
B.
hasBeachNearby
Indicates that one location is situated close enough to another location to have convenient access to a beach.
-
C.
hasCoastlineResort
Indicates that a geographic area or location contains a resort situated along its coastline.
-
D.
hasShoreNear
chosen
Indicates that one entity is located close enough to another entity’s shore or coastline to be considered nearby.
-
E.
hasIslandNearby
Indicates that one location is situated close to an island in geographic space.
- 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_69f349b5f6648190b9420d94a4cd16e0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffbf84f4948190b41a7bba07ae61ec |
completed | May 9, 2026, 11:13 p.m. |
| PD | Predicate disambiguation | batch_69ffbf0a59f88190870dbe25d8a63a00 |
completed | May 9, 2026, 11:11 p.m. |
Created at: May 1, 2026, 1:56 a.m.