Triple
T15147967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Edward the Martyr |
E361862
|
entity |
| Predicate | sainthoodReason |
P25961
|
FINISHED |
| Object | considered to have died unjustly and piously |
—
|
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: considered to have died unjustly and piously | Statement: [Saint Edward the Martyr, sainthoodReason, considered to have died unjustly and piously]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sainthoodReason Context triple: [Saint Edward the Martyr, sainthoodReason, considered to have died unjustly and piously]
-
A.
reasonForCanonization
chosen
Indicates the specific cause, miracle, virtue, or event that served as the basis for a person’s canonization.
-
B.
typeOfSaint
Indicates that one entity is classified as a specific kind or category of saint in relation to another entity.
-
C.
venerationOfSaints
Indicates the act of showing honor, reverence, or devotional respect toward saints.
-
D.
saintName
Indicates that an entity has the specified name under which they are recognized or venerated as a saint.
-
E.
religiousFigure
Indicates that one entity is recognized or designated as a religious leader, authority, or sacred person in relation to another entity.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005c825a481909d00098b0e743365 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:07 a.m.