Triple
T12703979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Bonneville |
E303531
|
entity |
| Predicate | maximumSurfaceArea |
P106433
|
FINISHED |
| Object | approximately 51,000 square 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 51,000 square kilometers | Statement: [Lake Bonneville, maximumSurfaceArea, approximately 51,000 square kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumSurfaceArea Context triple: [Lake Bonneville, maximumSurfaceArea, approximately 51,000 square kilometers]
-
A.
maximumMoundHeight
Indicates the greatest allowable or observed height of a mound relative to a specified reference or context.
-
B.
maximumNumber
Indicates that one entity specifies the highest allowable or observed quantity, value, or count associated with another entity.
-
C.
facesArea
Indicates that one entity is oriented toward, overlooks, or has its primary exposure directed toward a specified area.
-
D.
maximumCeiling
Indicates the highest allowable or achievable limit or value that something cannot exceed.
-
E.
maximumWeight
Indicates the greatest allowable or observed weight value associated with an entity or relationship.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69d96297b81c819081ad1432dc5f15f4 |
completed | April 10, 2026, 8:50 p.m. |
Created at: April 9, 2026, 5:23 p.m.