Triple
T20826232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple of Hera at Olympia |
E512706
|
entity |
| Predicate | hasNumberOfColumnsOnFacade |
P9588
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Temple of Hera at Olympia, hasNumberOfColumnsOnFacade, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfColumnsOnFacade Context triple: [Temple of Hera at Olympia, hasNumberOfColumnsOnFacade, 6]
-
A.
numberOfColumnsOnFacade
chosen
Indicates the count of vertical structural or decorative divisions (columns) present on a building’s facade.
-
B.
hasColumnCountBack
Indicates that an entity (such as a table or layout) has a specified number of columns on its back side or rear-facing section.
-
C.
numberOfColumns
Indicates the total count of vertical divisions (columns) associated with or contained in a given structure or dataset.
-
D.
hasColumns
Indicates that one entity possesses or is characterized by a set of columns associated with it.
-
E.
hasFrontColumns
Indicates that one entity possesses or features columns located at its front side.
- 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2fd8480819099930af691d97477 |
completed | April 21, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a1f4f48190aa9fb4ef8f8aea5a |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:41 p.m.