Triple
T10935080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ordonnance des cinq espèces de colonnes selon la méthode des Anciens |
E258310
|
entity |
| Predicate | numberOfColumnOrdersDiscussed |
P96711
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Ordonnance des cinq espèces de colonnes selon la méthode des Anciens, numberOfColumnOrdersDiscussed, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfColumnOrdersDiscussed Context triple: [Ordonnance des cinq espèces de colonnes selon la méthode des Anciens, numberOfColumnOrdersDiscussed, 5]
-
A.
columnOrder
Indicates the relative sequencing or arrangement of columns within a structured layout or dataset.
-
B.
columnOrderUsed
Indicates that a specific ordering of columns is applied or relied upon in a given context or operation.
-
C.
orderOf
Indicates that one entity is arranged, ranked, or sequenced before or after another according to a specified ordering criterion.
-
D.
hasColumnOrder
Indicates that one column in a sequence is positioned before or after another column, specifying their relative ordering.
-
E.
numberOfColumns
Indicates the total count of vertical divisions (columns) associated with or contained in a given structure or dataset.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770aee178819082c1671a37ff7d82 |
completed | April 9, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d7322370648190ba14cdd6fb4cdcb0 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:23 p.m.