Triple
T18763312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAM-4 |
E458829
|
entity |
| Predicate | hasRangeCategory |
P133442
|
FINISHED |
| Object | medium-range |
—
|
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: medium-range | Statement: [SAM-4, hasRangeCategory, medium-range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRangeCategory Context triple: [SAM-4, hasRangeCategory, medium-range]
-
A.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
B.
categoryRange
Indicates that a category or classification spans from a defined lower bound to an upper bound within a specified range.
-
C.
hasMajorRange
Indicates that one entity encompasses or defines the primary or most extensive range or scope associated with another entity.
-
D.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
-
E.
hasBandRange
Indicates that one entity has an associated range or span of bands (such as frequency or wavelength intervals) defined by the other entity.
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e58d80a954819083946dafc0c7af05 |
completed | April 20, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d0b7b708190877951b6e6cdcbc4 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49a9bcc0c81908df3e513fd6762ff |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 11:52 a.m.