Triple
T35573046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple F (Selinunte) |
E1027994
|
entity |
| Predicate | hasColumnStyle |
P1609
|
FINISHED |
| Object | fluted Doric 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: fluted Doric columns | Statement: [Temple F (Selinunte), hasColumnStyle, fluted Doric columns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColumnStyle Context triple: [Temple F (Selinunte), hasColumnStyle, fluted Doric columns]
-
A.
hasCol
Indicates that one entity possesses, contains, or is associated with a particular color.
-
B.
hasStyle
chosen
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
C.
hasRuleStyle
Indicates that an entity is associated with a particular rule-based style or formatting specification.
-
D.
hasColumns
Indicates that one entity possesses or is characterized by a set of columns associated with it.
-
E.
hasSystemStyle
Indicates that one entity is associated with, or characterized by, a particular system-defined style of another entity.
- 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_69f76e0386688190b931bacdc145938c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a04d8348190a4819666eab42c9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:04 p.m.