Triple
T28019791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C Track |
E707653
|
entity |
| Predicate | hasMinimumRadiusOption |
P51538
|
FINISHED |
| Object | R1 360 mm |
—
|
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: R1 360 mm | Statement: [C Track, hasMinimumRadiusOption, R1 360 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMinimumRadiusOption Context triple: [C Track, hasMinimumRadiusOption, R1 360 mm]
-
A.
hasRadiusRange
Indicates that there is a specified minimum and maximum radius within which the related entity or feature falls.
-
B.
hasRadiusType
Indicates that an entity has a radius characterized by a specific type or classification.
-
C.
minimumRadiusOfCurves
chosen
Indicates the smallest allowable radius for any curve in a path, track, or route associated with the subject.
-
D.
hasInnerEdgeRadius
Indicates that something possesses an inner edge characterized by a specific radius measurement.
-
E.
hasCoveringRadius
Indicates the maximum distance from any point in a space to the nearest point in a given set, defining how well that set covers the 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_69ef96baf3a881909a2b63844185dddd |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 27, 2026, 8:09 p.m.