Triple
T26773066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Getz Ice Shelf |
E670034
|
entity |
| Predicate | hasDynamicState |
P51622
|
FINISHED |
| Object | thinning |
—
|
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: thinning | Statement: [Getz Ice Shelf, hasDynamicState, thinning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDynamicState Context triple: [Getz Ice Shelf, hasDynamicState, thinning]
-
A.
hasStateSystem
Indicates that an entity possesses, follows, or is governed by a particular system of state organization, rules, or governance.
-
B.
hasDynamics
chosen
Indicates that one entity exhibits or is characterized by specific dynamic behavior, changes, or variations over time in relation to another entity or context.
-
C.
hasDynamicalClass
Indicates that an entity belongs to a specific category defined by its dynamical or motion-related behavior (e.g., orbital or kinematic characteristics).
-
D.
hasFamilyDynamic
Indicates the type or nature of the interpersonal relationships and interaction patterns that exist within a family unit.
-
E.
hasCoreState
Indicates that an entity possesses or is associated with a fundamental or primary state that defines its core condition or behavior.
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620debeb48190b7db395fb86cf8d9 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 4:03 a.m.