Triple
T282132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple of Apollo Epicurius at Bassae |
E5374
|
entity |
| Predicate | numberOfColumnsOnFlanks |
P9589
|
FINISHED |
| Object | 15 |
—
|
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: 15 | Statement: [Temple of Apollo Epicurius at Bassae, numberOfColumnsOnFlanks, 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfColumnsOnFlanks Context triple: [Temple of Apollo Epicurius at Bassae, numberOfColumnsOnFlanks, 15]
-
A.
numberOfStripes
Indicates the count of distinct stripe markings associated with an entity.
-
B.
numberOfSides
Indicates the relationship that specifies how many sides a given object or shape has.
-
C.
shaftCount
Indicates the number of shafts associated with or contained in an object or system.
-
D.
numberOfPositions
Indicates the total count of distinct positions or roles associated with a given entity.
-
E.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25e0c14b48190a5c936bab36180b3 |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b77e028819087e606fc321219f7 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25e06dd7c8190a8cbb76cee3c6e4b |
completed | Feb. 28, 2026, 3:16 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.