Triple
T6174523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acta Non Verba |
E137784
|
entity |
| Predicate | relatedPhrase |
P10003
|
FINISHED |
| Object | Facta non verba |
—
|
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: Facta non verba | Statement: [Acta Non Verba, relatedPhrase, Facta non verba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedPhrase Context triple: [Acta Non Verba, relatedPhrase, Facta non verba]
-
A.
associatedKeyword
Indicates that one entity is linked to or characterized by a particular keyword used for identification, categorization, or retrieval.
-
B.
linguisticallyRelatedTo
chosen
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
C.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
D.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
E.
definitionOfRelatedConcept
Indicates that one concept provides the formal meaning, explanation, or characterization of another closely related concept.
- 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_69c008a80f748190ba3d07ffc81acb29 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05dc55b5c819084482b735771c9a8 |
completed | March 22, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69c055f7f12881908e21c04e9b752ba4 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:18 p.m.