Triple
T9928734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keeler Gap |
E192587
|
entity |
| Predicate | hasParticleSizeRange |
P12465
|
FINISHED |
| Object | dust to meter-sized bodies |
—
|
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: dust to meter-sized bodies | Statement: [Keeler Gap, hasParticleSizeRange, dust to meter-sized bodies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParticleSizeRange Context triple: [Keeler Gap, hasParticleSizeRange, dust to meter-sized bodies]
-
A.
includesSizeRange
chosen
Indicates that one entity specifies or covers a particular range of sizes associated with another entity.
-
B.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
-
C.
grainSize
Indicates the relative coarseness or fineness of the material or particles involved in the relationship.
-
D.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
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.
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_69ca82dd978c8190947124ab0d3315ac |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb59d7ad08190982a1584547190bd |
completed | April 2, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69cd1d90b8a8819081748f129c0c6ab6 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:43 p.m.