Triple
T19658535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewis Glacier |
E472013
|
entity |
| Predicate | hasMeltSeason |
P1014
|
FINISHED |
| Object | late spring to summer melt season |
—
|
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: late spring to summer melt season | Statement: [Lewis Glacier, hasMeltSeason, late spring to summer melt season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeltSeason Context triple: [Lewis Glacier, hasMeltSeason, late spring to summer melt season]
-
A.
hasSeason
chosen
Indicates that an entity possesses, occurs during, or is associated with a particular season or set of seasons.
-
B.
canMelt
Indicates that one entity has the capability to melt another entity or substance under appropriate conditions.
-
C.
hasHotSeason
Indicates that an entity experiences a distinct period of time characterized by hot or high-temperature weather conditions.
-
D.
hasSeasonType
Indicates that something is associated with a particular category or type of season (e.g., summer, winter, rainy).
-
E.
hasFrozenInWinter
Indicates that something becomes or has become frozen during the winter season.
- 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.