Triple
T3646798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Mendota |
E77319
|
entity |
| Predicate | typicalIceCoverMonths |
P22448
|
FINISHED |
| Object | December to March |
—
|
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: December to March | Statement: [Lake Mendota, typicalIceCoverMonths, December to March]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalIceCoverMonths Context triple: [Lake Mendota, typicalIceCoverMonths, December to March]
-
A.
typicalIceThickness
Indicates the usual or characteristic thickness of ice under normal or representative conditions.
-
B.
hasTypicalIceRegime
chosen
Indicates that there is a characteristic or commonly occurring pattern of ice conditions associated with the referenced entity.
-
C.
snowCover
Indicates that one entity is covered by or blanketed with snow.
-
D.
hasIceSurface
Indicates that an entity possesses or is characterized by a surface composed primarily of ice.
-
E.
typicalSeaIceCondition
Indicates the usual or characteristic state or properties of sea ice under normal environmental 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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3895198819090a17a8894e91d00 |
completed | March 8, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69adb8445b2c8190ab07f6ad4e010d0e |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.