Triple
T1258957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knoxville Convention Center |
E12454
|
entity |
| Predicate | totalSpace |
P26320
|
FINISHED |
| Object | approximately 500,000 square feet |
—
|
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 500,000 square feet | Statement: [Knoxville Convention Center, totalSpace, approximately 500,000 square feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalSpace Context triple: [Knoxville Convention Center, totalSpace, approximately 500,000 square feet]
-
A.
totalCapacity
Indicates the maximum amount or volume that something can hold or accommodate in total.
-
B.
installedCapacity
Indicates the maximum output or production capability that has been set up or built for a system, facility, or equipment, typically measured under specified conditions.
-
C.
addressSpaceSize
Indicates the total amount of addressable memory or identifier range allocated or available within a given address space.
-
D.
maximumVolumeSize
Indicates the largest allowable size or capacity that a volume can have within a given system or context.
-
E.
stateSize
Indicates the relative or absolute physical extent or dimensions of a state, such as its area or population size.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc3a2848190891e73b351019d5b |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6eefbc81908dddd7d2ef368186 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd98b62c8190a5f6710345c0537d |
completed | March 1, 2026, 10:28 p.m. |
Created at: March 1, 2026, 7:50 p.m.