Triple
T23244091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cepheid variables |
E581535
|
entity |
| Predicate | hasCauseOfVariability |
P151508
|
FINISHED |
| Object | pulsation of stellar envelope |
—
|
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: pulsation of stellar envelope | Statement: [Cepheid variables, hasCauseOfVariability, pulsation of stellar envelope]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCauseOfVariability Context triple: [Cepheid variables, hasCauseOfVariability, pulsation of stellar envelope]
-
A.
hasVariability
Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
-
B.
hasVariance
Indicates that there is a measurable degree of variability or dispersion in the values or outcomes associated with the related entities.
-
C.
variabilityRecognizedIn
Indicates that variability or variation in one entity is acknowledged, identified, or detected within the context of another entity.
-
D.
hasVariabilityType
Indicates that an entity is associated with a specific kind or category of variability (e.g., how or in what way it varies).
-
E.
hasSpectralVariability
Indicates that an entity exhibits changes or fluctuations in its spectral properties over time or under different conditions.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f192efd44c8190b179b4d1cb71efa5 |
completed | April 29, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69effcdadec0819092ec1749ee453b4e |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:10 p.m.