Triple
T5919433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nunc Dimittis |
E131664
|
entity |
| Predicate | hasEnglishIncipit |
P67696
|
FINISHED |
| Object | Lord, now lettest Thou Thy servant depart in peace |
—
|
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: Lord, now lettest Thou Thy servant depart in peace | Statement: [Nunc Dimittis, hasEnglishIncipit, Lord, now lettest Thou Thy servant depart in peace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnglishIncipit Context triple: [Nunc Dimittis, hasEnglishIncipit, Lord, now lettest Thou Thy servant depart in peace]
-
A.
hasEnglishEdition
Indicates that one entity has a version or edition of itself that is produced or available in the English language.
-
B.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
C.
hasEnglishReception
Indicates that something has been received, interpreted, or responded to within an English-speaking context.
-
D.
firstEditionLanguage
Indicates the language in which a work was originally published in its first edition.
-
E.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
- 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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c048fc112c8190b905bf561c9de096 |
completed | March 22, 2026, 7:54 p.m. |
| PD | Predicate disambiguation | batch_69c03352208c8190968efed05a9fd416 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c048fb02a081908e78629e1e283cd0 |
completed | March 22, 2026, 7:54 p.m. |
Created at: March 22, 2026, 4 p.m.