Triple
T30785421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gap Cathedral |
E783942
|
entity |
| Predicate | regionRelativeLocation |
P7317
|
FINISHED |
| Object | southeastern France |
—
|
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: southeastern France | Statement: [Gap Cathedral, regionRelativeLocation, southeastern France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionRelativeLocation Context triple: [Gap Cathedral, regionRelativeLocation, southeastern France]
-
A.
relativePosition
Indicates the spatial relationship of one entity’s location with respect to another entity’s position.
-
B.
hasRelativeLocation
chosen
Indicates that one entity is positioned in space in relation to another entity’s location.
-
C.
relativePositioning
Indicates how one entity is spatially arranged or located in relation to another entity.
-
D.
locationRelativeToBorder
Indicates the position or placement of something in relation to a specified border or boundary.
-
E.
positionRelativeToTown
Indicates the spatial position or orientation of one place or object in relation to a specified town.
- 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe5ec9028081909ae3d6fbe2f4cbbc |
completed | May 8, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69fe5e1d715881909fc516fafc707644 |
completed | May 8, 2026, 10:05 p.m. |
Created at: April 29, 2026, 8:41 p.m.