Triple
T12668324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hail Holy Queen |
E302613
|
entity |
| Predicate | hasOpeningWordsLatin |
P90624
|
FINISHED |
| Object | Salve, Regina, mater misericordiae |
—
|
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: Salve, Regina, mater misericordiae | Statement: [Hail Holy Queen, hasOpeningWordsLatin, Salve, Regina, mater misericordiae]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpeningWordsLatin Context triple: [Hail Holy Queen, hasOpeningWordsLatin, Salve, Regina, mater misericordiae]
-
A.
openingWordsLatin
chosen
Indicates that the opening words of a text, work, or document are expressed in Latin.
-
B.
correspondsToLatinWord
Indicates that one element is the equivalent or matching term of another element in Latin.
-
C.
hasLatinInfluence
Indicates that one entity exerts or reflects cultural, linguistic, or stylistic influence derived from Latin on another entity.
-
D.
hasOpeningVerseMeaning
Indicates that something (such as a text, song, or poem) possesses an opening verse that conveys a particular meaning or message.
-
E.
usesLatinAlphabetSince
Indicates that an entity has employed the Latin alphabet as its writing system starting from a specific point in time and continuing thereafter.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.