Triple
T3934764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olathe, Kansas |
E90881
|
entity |
| Predicate | averageAnnualSnowfallInches |
P10513
|
FINISHED |
| Object | about 20 |
—
|
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: about 20 | Statement: [Olathe, Kansas, averageAnnualSnowfallInches, about 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageAnnualSnowfallInches Context triple: [Olathe, Kansas, averageAnnualSnowfallInches, about 20]
-
A.
averageAnnualSnowfall
chosen
Indicates the typical amount of snow that falls in a given location over the course of a year, averaged across multiple years.
-
B.
averageAnnualPrecipitation
Indicates the typical total amount of precipitation an entity receives over the course of a year, averaged across multiple years.
-
C.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
D.
snowfallRecord
Indicates that a specific amount of snow has been measured or documented for a particular place and time.
-
E.
snowCover
Indicates that one entity is covered by or blanketed with snow.
- 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_69aed95f26e0819094b0e71974543a19 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeedcbf0188190a5e828707a77752a |
completed | March 9, 2026, 3:57 p.m. |
| PD | Predicate disambiguation | batch_69aee7625ad4819097e4e8a168c19274 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:23 p.m.