Triple
T6381395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alboran gyre |
E143589
|
entity |
| Predicate | hasTemporalStability |
P15684
|
FINISHED |
| Object | quasi-permanent |
—
|
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: quasi-permanent | Statement: [Alboran gyre, hasTemporalStability, quasi-permanent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTemporalStability Context triple: [Alboran gyre, hasTemporalStability, quasi-permanent]
-
A.
hasTemporalUse
Indicates that something is used, applicable, or valid only during a specific time or temporal interval.
-
B.
isStable
Indicates that the state, condition, or configuration of an entity does not change significantly over time or under expected variations in its environment.
-
C.
hasTemporalClassification
Indicates a relationship where something is assigned or associated with a specific temporal category, period, or time-based classification.
-
D.
hasStabilityLevel
chosen
Indicates that something possesses a particular degree or state of stability, often quantified or categorized along a defined scale.
-
E.
hasTemporalRole
Indicates that an entity participates in a role or function that is defined, constrained, or characterized by a specific time or temporal context.
- F. None of above.
Provenance (3 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_69c008dac1ec81909cef8157ccd69962 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0685385948190938b67bff671072b |
completed | March 22, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69c060eff524819094cee1c70a0c1ff4 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:33 p.m.