Triple
T19658514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewis Glacier |
E472013
|
entity |
| Predicate | hasThicknessTrend |
P60169
|
FINISHED |
| Object | decreasing thickness |
—
|
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: decreasing thickness | Statement: [Lewis Glacier, hasThicknessTrend, decreasing thickness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThicknessTrend Context triple: [Lewis Glacier, hasThicknessTrend, decreasing thickness]
-
A.
hasTrend
Indicates that something exhibits or is associated with a particular pattern of change or direction over time.
-
B.
sizeTrend
chosen
Indicates how the size of an entity changes over time or relative to another entity (e.g., increasing, decreasing, or remaining stable).
-
C.
thickness
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
-
D.
hasStratigraphicThickness
Indicates the measured vertical thickness or depth extent of a stratigraphic unit or layer.
-
E.
hasTendency
Indicates that an entity is inclined or likely to exhibit a particular behavior, characteristic, or outcome under certain conditions.
- 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641485ce481908b3860fa5e3a9f6e |
completed | April 20, 2026, 3:07 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:45 p.m.