Triple
T19030189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Latin Pascha |
E465714
|
entity |
| Predicate | usedToTranslate |
P133625
|
FINISHED |
| Object | Greek Πάσχα in Christian texts |
—
|
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: Greek Πάσχα in Christian texts | Statement: [Latin Pascha, usedToTranslate, Greek Πάσχα in Christian texts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToTranslate Context triple: [Latin Pascha, usedToTranslate, Greek Πάσχα in Christian texts]
-
A.
translationUsedAs
Indicates that one translation of a text, phrase, or term is employed or treated as another specific translation in a given context.
-
B.
laterTranslatedAs
Indicates that something was translated at a later time into a different language, form, or version under a specified title or expression.
-
C.
hasTranslated
Indicates that one entity has rendered the content of another entity from one language into a different language.
-
D.
translatedIn
Indicates that a work, text, or content has been rendered from its original language into another specified language or linguistic form.
-
E.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d73f98dc81909acbb366f00d2d54 |
completed | April 20, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8f6f7c8190af645bf08823ee2b |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 12:02 p.m.