Triple
T60680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Superior |
E1205
|
entity |
| Predicate | hasVolume |
P1567
|
FINISHED |
| Object | approximately 12,100 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 12,100 cubic kilometers | Statement: [Lake Superior, hasVolume, approximately 12,100 cubic kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVolume Context triple: [Lake Superior, hasVolume, approximately 12,100 cubic kilometers]
-
A.
volume
chosen
Indicates the amount of three-dimensional space an entity occupies or contains.
-
B.
numberOfVolumes
Indicates the total count of separate volumes or parts that make up a multi-volume work or collection.
-
C.
canHold
Indicates that one entity has the capacity or ability to contain, support, or carry another entity.
-
D.
isBoundVolumeSeries
Indicates that one entity is a series composed of multiple bound volumes that are physically or conceptually grouped together.
-
E.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a251a1b8ac8190b44be4c3c41e5681 |
completed | Feb. 28, 2026, 2:23 a.m. |
| PD | Predicate disambiguation | batch_69a24ea0bec48190b2af1fb287e9e692 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.