Triple
T2916190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMARTS 1.5-meter Telescope |
E78611
|
entity |
| Predicate | hasSizeClass |
P23656
|
FINISHED |
| Object | medium-sized telescope |
—
|
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-sized telescope | Statement: [SMARTS 1.5-meter Telescope, hasSizeClass, medium-sized telescope]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSizeClass Context triple: [SMARTS 1.5-meter Telescope, hasSizeClass, medium-sized telescope]
-
A.
hasSize
Indicates that one entity possesses a particular physical magnitude or extent, such as length, volume, or overall dimensions.
-
B.
hasRelativeSize
Indicates that one entity’s size is being compared to another entity’s size, expressing a relative rather than absolute magnitude.
-
C.
includesSizeRange
Indicates that one entity specifies or covers a particular range of sizes associated with another entity.
-
D.
hasMinimumSize
Indicates that an entity meets or exceeds a specified minimum size threshold.
-
E.
heightClass
chosen
Indicates the categorical height level or range to which an entity is assigned (e.g., short, medium, tall).
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:53 p.m.