Triple
T3408728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vernadsky Research Base |
E71837
|
entity |
| Predicate | hasAtmosphericRecord |
P49125
|
FINISHED |
| Object | long-term ozone data series |
—
|
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: long-term ozone data series | Statement: [Vernadsky Research Base, hasAtmosphericRecord, long-term ozone data series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAtmosphericRecord Context triple: [Vernadsky Research Base, hasAtmosphericRecord, long-term ozone data series]
-
A.
hasAtmosphere
Indicates that an astronomical body possesses a surrounding layer of gases held by its gravity.
-
B.
hasAtmosphericFeature
Indicates that one entity possesses or exhibits a particular feature or characteristic of its atmosphere.
-
C.
atmosphericStudyType
Indicates the specific kind or category of study being conducted on the atmosphere or atmospheric phenomena.
-
D.
hasMainAtmosphericComponent
Indicates that one entity has another entity as the primary constituent of its atmosphere.
-
E.
capturesAtmosphereOf
Indicates that one entity successfully conveys or reflects the overall mood, tone, or ambiance characteristic of another 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_69ad85ac312481909e7027ced1456a9f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9056acc8190a9c50ec374851ac8 |
completed | March 8, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69adadfa73ac8190a163f93e88d217f8 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb21a437c81908bca88d5e123d744 |
completed | March 8, 2026, 5:30 p.m. |
Created at: March 8, 2026, 3:15 p.m.