Triple
T10736299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toledo School of Translators |
E253203
|
entity |
| Predicate | languageOfTargetTexts |
P52478
|
FINISHED |
| Object | Latin |
—
|
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: Latin | Statement: [Toledo School of Translators, languageOfTargetTexts, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfTargetTexts Context triple: [Toledo School of Translators, languageOfTargetTexts, Latin]
-
A.
targetLanguage
Indicates the language that is the intended recipient or focus of a communication, translation, or linguistic operation.
-
B.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
C.
translationTargetLanguage
Indicates the language into which content is being or has been translated.
-
D.
languageOfTranslations
chosen
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
-
E.
contentLanguage
Indicates the language in which the content is expressed or intended to be understood.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d71022aee0819091a5790d3dee6777 |
completed | April 9, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69d6f309a44881908e49e3ba478c35b4 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:14 p.m.