Triple
T2969881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michelangelo's Sistine Chapel ceiling frescoes |
E80253
|
entity |
| Predicate | dimensionNote |
P45295
|
FINISHED |
| Object | covers most of the Sistine Chapel ceiling |
—
|
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: covers most of the Sistine Chapel ceiling | Statement: [Michelangelo's Sistine Chapel ceiling frescoes, dimensionNote, covers most of the Sistine Chapel ceiling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionNote Context triple: [Michelangelo's Sistine Chapel ceiling frescoes, dimensionNote, covers most of the Sistine Chapel ceiling]
-
A.
dimensionType
Indicates the specific kind or category of dimension that characterizes how something is measured or structured.
-
B.
dimension
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
C.
dimensionSymbol
Indicates a symbolic notation that represents or labels a specific dimension or measurement attribute in a context.
-
D.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
E.
dimensionEquals
Indicates that two entities have exactly the same dimensional properties or measurements.
- 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad997282b481909d078be0e70d9930 |
completed | March 8, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69ad960e71f8819088179d11248c6ed0 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad98379fac8190a4dfe530787703c9 |
completed | March 8, 2026, 3:39 p.m. |
Created at: March 8, 2026, 2:58 p.m.