Triple
T337509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pantheon |
E6760
|
entity |
| Predicate | hasPorticoColumns |
P6684
|
FINISHED |
| Object | 16 Corinthian columns |
—
|
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: 16 Corinthian columns | Statement: [Pantheon, hasPorticoColumns, 16 Corinthian columns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPorticoColumns Context triple: [Pantheon, hasPorticoColumns, 16 Corinthian columns]
-
A.
hasPortico
Indicates that one entity (typically a building or structure) features a portico as part of its architectural design.
-
B.
hasMezzanine
Indicates that one entity includes or is equipped with a mezzanine level in relation to another entity.
-
C.
hasCorridor
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
D.
hasArchitecturalFeature
chosen
Indicates that one entity possesses, includes, or is characterized by a specific architectural feature or element.
-
E.
hasNumberOfEntrances
Indicates the relationship that specifies how many entrances an entity possesses.
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eae23b0c819081f8bf9ac26685ab |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e94f049881908f10bb6548a8bb2e |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.