Triple
T15716563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kepler-186f |
E380974
|
entity |
| Predicate | followUpStudies |
P119896
|
FINISHED |
| Object | atmospheric and climate modeling in scientific literature |
—
|
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: atmospheric and climate modeling in scientific literature | Statement: [Kepler-186f, followUpStudies, atmospheric and climate modeling in scientific literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followUpStudies Context triple: [Kepler-186f, followUpStudies, atmospheric and climate modeling in scientific literature]
-
A.
relatedStudy
Indicates that one study is connected or relevant to another study, typically through shared topics, methods, or findings.
-
B.
feasibilityStudiesBy
Indicates that feasibility studies are conducted or authored by a specified agent or entity.
-
C.
coordinatesClinicalTrialsFor
Indicates that one entity organizes, manages, or oversees the planning and execution of clinical trials on behalf of another entity.
-
D.
hasClinicalTrialsIn
Indicates that clinical trials related to an entity are being or have been conducted in a specified location or region.
-
E.
studiesProcess
Indicates that an entity systematically examines, researches, or learns about a particular process.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f91beb08190bd91bf9306737c3b |
completed | April 16, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e0094af5b481908ad51d5d7ba0c726 |
completed | April 15, 2026, 9:55 p.m. |
Created at: April 10, 2026, 4:45 a.m.