Triple
T2278537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Totus Tuus |
E51227
|
entity |
| Predicate | longFormTranslation |
P25592
|
FINISHED |
| Object | I am all yours, and all that I have is yours |
—
|
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: I am all yours, and all that I have is yours | Statement: [Totus Tuus, longFormTranslation, I am all yours, and all that I have is yours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: longFormTranslation Context triple: [Totus Tuus, longFormTranslation, I am all yours, and all that I have is yours]
-
A.
translationMethod
Indicates the technique or process used to translate content from one language or form to another.
-
B.
translationOfOpeningWords
chosen
Indicates that one text is a translation of the initial words or opening phrase of another text.
-
C.
translationOfOfficialName
Indicates that one name is an official translation of another name in a different language.
-
D.
translationDirection
Indicates the source and target languages involved in a translation, specifying the direction from the original language to the translated language.
-
E.
textOpeningTranslation
Indicates that a text serves as a translation of the opening section of another text.
- 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_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc217b6648190be77d2176d322efd |
completed | March 7, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69abbdb9aa3c819088d0316c5269a1c2 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.