Triple
T12703981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Bonneville |
E303531
|
entity |
| Predicate | maximumVolume |
P12009
|
FINISHED |
| Object | approximately 9,500 cubic kilometers |
—
|
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: approximately 9,500 cubic kilometers | Statement: [Lake Bonneville, maximumVolume, approximately 9,500 cubic kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumVolume Context triple: [Lake Bonneville, maximumVolume, approximately 9,500 cubic kilometers]
-
A.
maximumVolumeSize
chosen
Indicates the largest allowable size or capacity that a volume can have within a given system or context.
-
B.
maximumBrightness
Indicates the highest level of brightness that an entity can reach or exhibit.
-
C.
maximumCeiling
Indicates the highest allowable or achievable limit or value that something cannot exceed.
-
D.
maximumResolution
Indicates the highest level of detail or fineness at which something (such as an image, display, or measurement) can be represented or processed.
-
E.
maximumIntensity
Indicates the greatest level or strength that a quantity, effect, or signal can reach within a given context.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d962a32c6481908ddaddae4ea267bf |
completed | April 10, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69d960be63f081908a5ef5ef17a311bf |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:23 p.m.