Triple
T19886601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cygnus OB2 association |
E477914
|
entity |
| Predicate | hasAssociatedPhenomenon |
P137709
|
FINISHED |
| Object | strong stellar winds |
—
|
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: strong stellar winds | Statement: [Cygnus OB2 association, hasAssociatedPhenomenon, strong stellar winds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedPhenomenon Context triple: [Cygnus OB2 association, hasAssociatedPhenomenon, strong stellar winds]
-
A.
affectsPhenomenon
Indicates that one phenomenon produces an influence or change on another phenomenon.
-
B.
capturesPhenomenon
Indicates that one entity records, represents, or effectively reflects the occurrence or characteristics of a particular phenomenon.
-
C.
associatedWithPhenotype
Indicates that an entity has a documented connection or correlation with a particular phenotype or observable trait.
-
D.
examplePhenomenon
Indicates a representative or illustrative occurrence used to demonstrate or clarify a broader phenomenon or pattern.
-
E.
hasAssociatedDisease
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
- 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65909fe0481908e22b60d04fe2b11 |
completed | April 20, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:52 p.m.