Triple
T1051946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palaestra of Olympia |
E22717
|
entity |
| Predicate | hasApproximateDimensions |
P18961
|
FINISHED |
| Object | 66 meters per side |
—
|
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: 66 meters per side | Statement: [Palaestra of Olympia, hasApproximateDimensions, 66 meters per side]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateDimensions Context triple: [Palaestra of Olympia, hasApproximateDimensions, 66 meters per side]
-
A.
hasDimensionsApprox
chosen
Indicates that an entity has physical dimensions that are known only approximately, rather than as exact measurements.
-
B.
hasApproximateExtent
Indicates that one entity has a spatial, temporal, or quantitative extent that is only roughly or approximately specified rather than exact.
-
C.
approximateSize
Indicates that one entity has a size that is roughly or approximately equal to the size of another entity.
-
D.
hasApproximateDistanceScale
Indicates that one entity is related to another by a distance measure that is approximate or estimated rather than exact.
-
E.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b5312081909796df58fa7c1e9d |
completed | March 1, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69a4b7309cc481908ed839b0b8d75dbf |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.