Triple
T25133718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monts de la Madeleine |
E629598
|
entity |
| Predicate | naturalBoundaryBetween |
P39423
|
FINISHED |
| Object | Loire department |
—
|
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: Loire department | Statement: [Monts de la Madeleine, naturalBoundaryBetween, Loire department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: naturalBoundaryBetween Context triple: [Monts de la Madeleine, naturalBoundaryBetween, Loire department]
-
A.
boundaryBetween
chosen
Indicates that something serves as a dividing line or limit separating two distinct regions, areas, or entities.
-
B.
stateBoundaryBetween
Indicates a boundary line that separates or lies between two states.
-
C.
fareBoundaryBetween
Indicates that there is a dividing line or zone where one fare region, zone, or pricing scheme ends and another begins.
-
D.
climateBoundaryBetween
Indicates a boundary or dividing line between two regions that differ in climate characteristics or classifications.
-
E.
borderDefinedBetween
Indicates that a boundary line or border is formally established between two geographic or political entities.
- 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_69e2ff338250819096ff6c8892804389 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 6:28 a.m.