Triple
T21569796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Champs magnétiques |
E532253
|
entity |
| Predicate | circaLength |
P144287
|
FINISHED |
| Object | short book |
—
|
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: short book | Statement: [Les Champs magnétiques, circaLength, short book]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: circaLength Context triple: [Les Champs magnétiques, circaLength, short book]
-
A.
circaDuration
Indicates an approximate or uncertain duration of time associated with an event, state, or relationship.
-
B.
circumference
Indicates the total length around the boundary of a closed curve, typically a circle, relating a shape to the measure of its perimeter.
-
C.
isCircumferential
Indicates that something extends or is positioned all the way around the boundary or perimeter of another object or area.
-
D.
archLength
Indicates the measured length of an arch-shaped structure or path between two defined points.
-
E.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
- F. None of above. chosen
Provenance (4 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_69e0c460db088190828c64206a450273 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eee9cb9718819094fc95b25df68bd1 |
completed | April 27, 2026, 4:44 a.m. |
| PD | Predicate disambiguation | batch_69e6320c8c2c81908bf031447d66a052 |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e633bf34c481909925d8dc1a633a65 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 16, 2026, 6:30 p.m.