Triple
T19561042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clarence Island ice cap |
E489449
|
entity |
| Predicate | hasStability |
P81575
|
FINISHED |
| Object | largely stable |
—
|
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: largely stable | Statement: [Clarence Island ice cap, hasStability, largely stable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStability Context triple: [Clarence Island ice cap, hasStability, largely stable]
-
A.
hasStabilityLevel
Indicates that something possesses a particular degree or state of stability, often quantified or categorized along a defined scale.
-
B.
haveStabilityDeterminedBy
Indicates that the stability of one entity is determined or governed by another specified factor or entity.
-
C.
isStable
Indicates that the state, condition, or configuration of an entity does not change significantly over time or under expected variations in its environment.
-
D.
hasStabilityIndex
Indicates that an entity is associated with a specific measure or score representing its level of stability.
-
E.
stabilityDescription
chosen
Indicates how stable, consistent, or enduring the relationship, condition, or state between the entities is over time.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f7442e08190ad030151ec0a97d4 |
completed | April 20, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:42 p.m.