Triple
T1159119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trisagion Hymn |
E24454
|
entity |
| Predicate | translationOfOpeningWords |
P25592
|
FINISHED |
| Object | Holy God, Holy Mighty, Holy Immortal, have mercy on us |
—
|
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: Holy God, Holy Mighty, Holy Immortal, have mercy on us | Statement: [Trisagion Hymn, translationOfOpeningWords, Holy God, Holy Mighty, Holy Immortal, have mercy on us]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: translationOfOpeningWords Context triple: [Trisagion Hymn, translationOfOpeningWords, Holy God, Holy Mighty, Holy Immortal, have mercy on us]
-
A.
translationOfMotto
Indicates that one motto is a translation of another motto in a different language.
-
B.
translationApproximate
Indicates that one entity is an inexact or approximate translation of another, preserving general meaning but not precise wording or full detail.
-
C.
translationDirection
Indicates the source and target languages involved in a translation, specifying the direction from the original language to the translated language.
-
D.
firstLineTranslation
Indicates that one text is a translation of the first line of another text.
-
E.
translationMethod
Indicates the technique or process used to translate content from one language or form to another.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcad47a08190895769611798f67f |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb525b648190adcb7a29256d3c41 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc49693c8190978ec63a5171d342 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:45 p.m.