Triple
T18971378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Sioux Reservation |
E464176
|
entity |
| Predicate | originalAreaApprox |
P128175
|
FINISHED |
| Object | over 60 million acres |
—
|
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: over 60 million acres | Statement: [Great Sioux Reservation, originalAreaApprox, over 60 million acres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalAreaApprox Context triple: [Great Sioux Reservation, originalAreaApprox, over 60 million acres]
-
A.
areaApprox
Indicates that one entity’s area is approximately equal to the area of another entity.
-
B.
hasApproximateSurfaceArea
chosen
Indicates that an entity is associated with a surface area value that is an estimate rather than an exact measurement.
-
C.
representedArea
Indicates that one entity serves as a representation or depiction of a particular area or region.
-
D.
coveredArea
Indicates that one entity occupies or extends over a specific spatial region or surface area associated with another entity.
-
E.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
- 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d61a8bbc8190881908a71e0f2a53 |
completed | April 20, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, noon