Triple
T9216739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lady of the Angels |
E221258
|
entity |
| Predicate | invocationForm |
P57113
|
FINISHED |
| Object | prayers for angelic protection |
—
|
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: prayers for angelic protection | Statement: [Our Lady of the Angels, invocationForm, prayers for angelic protection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: invocationForm Context triple: [Our Lady of the Angels, invocationForm, prayers for angelic protection]
-
A.
invocationOf
chosen
Indicates that one entity is the act, event, or instance of calling upon, summoning, or appealing to another entity (such as a function, service, or authority) to perform its role or be brought into effect.
-
B.
invocationType
Indicates the manner or mode in which an action, function, or process is called, triggered, or executed.
-
C.
usesForm
Indicates that one entity employs, applies, or operates through a particular form, format, or structured representation of something.
-
D.
dialogueForm
Indicates that one entity takes the form or structure of a dialogue, typically involving conversational or interactive exchange between parties.
-
E.
implementationForm
Indicates the specific manner, format, or method by which something is implemented or realized in practice.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda096358819096d4e790da057512 |
completed | April 1, 2026, 8:40 a.m. |
| PD | Predicate disambiguation | batch_69cc660ce23c81909c7bbe10f4a05f36 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:27 p.m.