Triple
T29056972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ozone Monitoring Instrument |
E735411
|
entity |
| Predicate | globalCoverageFrequency |
P165967
|
FINISHED |
| Object | daily |
—
|
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: daily | Statement: [Ozone Monitoring Instrument, globalCoverageFrequency, daily]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: globalCoverageFrequency Context triple: [Ozone Monitoring Instrument, globalCoverageFrequency, daily]
-
A.
componentCoverage
Indicates that one entity provides coverage, protection, or support for another as one of its components or constituent parts.
-
B.
hasFrequencyCoverage
Indicates that one entity provides, supports, or is applicable across a specified range or set of frequencies associated with another entity.
-
C.
branchCoverage
Indicates that one entity measures or represents how many decision branches in another entity’s control flow have been executed during testing.
-
D.
formatCoverage
Indicates how thoroughly or extensively a particular format or formatting scheme is applied or supported in a given context.
-
E.
registerCoverage
Indicates recording or enrolling an entity under a specified coverage or protection plan.
- 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_69f077e85498819088b65186550da8cd |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6609311d081908c4eee11d1284fab |
completed | May 2, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65ad638ac8190a17bb987fce53279 |
completed | May 2, 2026, 8:13 p.m. |
Created at: April 28, 2026, 10:12 a.m.