Triple
T21180027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine McAuley |
E521921
|
entity |
| Predicate | causeOfBeatification |
P25961
|
FINISHED |
| Object | heroic virtue |
—
|
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: heroic virtue | Statement: [Catherine McAuley, causeOfBeatification, heroic virtue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfBeatification Context triple: [Catherine McAuley, causeOfBeatification, heroic virtue]
-
A.
causeForBeatificationOpened
Indicates that an official ecclesiastical process has been initiated to investigate a person’s life and virtues as a potential cause for beatification.
-
B.
beatificationDate
Indicates the date on which a person was officially declared blessed (beatified) in a religious context.
-
C.
placeOfBeatification
Indicates the location where a person was formally declared beatified in a religious context.
-
D.
yearCauseForCanonizationOpened
Indicates the year in which the formal process or cause for an entity’s canonization was officially opened.
-
E.
reasonForCanonization
chosen
Indicates the specific cause, miracle, virtue, or event that served as the basis for a person’s canonization.
- 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_69e0b50ef1d48190b063aa342667df22 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7301c842c8190b969a8b3f194003a |
completed | April 21, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69e5f6027c248190a170a36612bd337e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:01 p.m.