Triple
T7692428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dona Nobis Pacem |
E174280
|
entity |
| Predicate | textOrigin |
P58596
|
FINISHED |
| Object | Agnus Dei section of the Mass |
—
|
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: Agnus Dei section of the Mass | Statement: [Dona Nobis Pacem, textOrigin, Agnus Dei section of the Mass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textOrigin Context triple: [Dona Nobis Pacem, textOrigin, Agnus Dei section of the Mass]
-
A.
originalText
Indicates that one text is the initial, unmodified version from which other versions, translations, or representations are derived.
-
B.
originalTextLanguage
Indicates the language in which a text was originally written or created before any translation or adaptation.
-
C.
physicalOrigin
Indicates that one entity is the place or source from which another entity physically originates or comes into existence.
-
D.
originalFor
chosen
Indicates that one entity serves as the source, basis, or prototype from which another entity is derived, adapted, or created.
-
E.
originalTextOn
Indicates that a piece of original text is physically or logically located on a particular medium, surface, or object.
- 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:02 p.m.