Triple
T10185695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Historia Monachorum in Aegypto |
E236902
|
entity |
| Predicate | hasTranslationLanguage |
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: [Historia Monachorum in Aegypto, hasTranslationLanguage, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTranslationLanguage Context triple: [Historia Monachorum in Aegypto, hasTranslationLanguage, Latin]
-
A.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
hasTranslated
Indicates that one entity has rendered the content of another entity from one language into a different language.
-
C.
hasTranslationBase
Indicates that one entity serves as the original source or base text from which the other entity is translated.
-
D.
hasTranslationPlatform
Indicates that one entity provides or is associated with a platform used to perform or manage translations for another entity.
-
E.
languageOfTranslations
chosen
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded36e9808190b385c5aec4889e00 |
completed | April 2, 2026, 4:14 a.m. |
| PD | Predicate disambiguation | batch_69cd7c79f21c8190a7f31b2eab80b8ba |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:12 p.m.