Triple
T1050077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Concilio et Labore |
E22675
|
entity |
| Predicate | traditionalTranslation |
P21030
|
FINISHED |
| Object | By wisdom and effort |
—
|
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: By wisdom and effort | Statement: [Concilio et Labore, traditionalTranslation, By wisdom and effort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalTranslation Context triple: [Concilio et Labore, traditionalTranslation, By wisdom and effort]
-
A.
translationMethod
Indicates the technique or process used to translate content from one language or form to another.
-
B.
translator
Indicates that one entity serves to convert or render content from one language or form into another for a second entity.
-
C.
traditionalLanguageName
chosen
Indicates the name traditionally used in a particular language to refer to the subject entity.
-
D.
inscriptionTranslation
Indicates that a provided text expresses the translated content of a specific inscription.
-
E.
translationDirection
Indicates the source and target languages involved in a translation, specifying the direction from the original language to the translated language.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b2c6208190b6fdf3e93b1b1d04 |
completed | March 1, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69a4b7309cc481908ed839b0b8d75dbf |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.