Triple
T29510530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hephaesteum |
E748635
|
entity |
| Predicate | hasColumnCountPerSide |
P202296
|
FINISHED |
| Object | 6 x 13 |
—
|
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 x 13 | Statement: [Hephaesteum, hasColumnCountPerSide, 6 x 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColumnCountPerSide Context triple: [Hephaesteum, hasColumnCountPerSide, 6 x 13]
-
A.
hasNumberOfColumnsOnLongSide
Indicates the relationship that specifies how many columns are present along the longer side of an object or structure.
-
B.
numberOfColumnsPerShortSide
Indicates the count of columns that appear along each of the shorter sides of a rectangular or similarly shaped structure or layout.
-
C.
hasNumberOfSquares
Indicates that an entity is associated with a specific count of squares it contains or comprises.
-
D.
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.
-
E.
numberOfColumnsOnFlanks
Indicates the count of columns located on the flanking sides of a structure or object.
- 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_69f0bd461c208190bec20bbf24e02cc5 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_6a006fe981488190b4287289a3327664 |
completed | May 10, 2026, 11:45 a.m. |
| PD | Predicate disambiguation | batch_6a006f6976ec8190ba2c04fbaa946345 |
completed | May 10, 2026, 11:43 a.m. |
| PDg | Predicate description generation | batch_6a006fe8d7ac81908642e4b7c81532ac |
completed | May 10, 2026, 11:45 a.m. |
Created at: April 28, 2026, 4:32 p.m.