Triple
T18198873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESPaDOnS |
E435729
|
entity |
| Predicate | resolvingPower |
P7238
|
FINISHED |
| Object | up to about 65,000 |
—
|
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: up to about 65,000 | Statement: [ESPaDOnS, resolvingPower, up to about 65,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resolvingPower Context triple: [ESPaDOnS, resolvingPower, up to about 65,000]
-
A.
spectralResolution
chosen
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
-
B.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
-
C.
resolutionOf
Indicates that one entity is the formal decision, outcome, or solution produced in response to, or for the purpose of addressing, another entity such as an issue, proposal, or problem.
-
D.
typicalMagnification
Indicates the usual or characteristic degree to which something is enlarged or magnified under normal or standard conditions.
-
E.
viewfinderResolution
Indicates the resolution or level of detail provided by a device’s viewfinder display.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d545f4819090285d1446bd3c27 |
completed | April 19, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.