Triple
T1237689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Catholic biblical canon |
E26582
|
entity |
| Predicate | differsFromProtestantCanonInOldTestamentBooks |
P2306
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Roman Catholic biblical canon, differsFromProtestantCanonInOldTestamentBooks, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: differsFromProtestantCanonInOldTestamentBooks Context triple: [Roman Catholic biblical canon, differsFromProtestantCanonInOldTestamentBooks, yes]
-
A.
inChristianCanonOrder
Indicates that the entities are arranged according to the sequence used in the Christian biblical canon.
-
B.
excludesDeuterocanonicalBooksIn
chosen
Indicates that a canon, edition, or tradition omits the Deuterocanonical books from a specified scriptural collection or corpus.
-
C.
doesNotRecognizeAsScripture
Indicates that one entity does not accept or acknowledge another entity as authoritative scripture.
-
D.
textSourceApocrypha
Indicates that the referenced text originates from or is classified as apocryphal writings.
-
E.
numberOfCanonicalGospels
Indicates the count of canonical gospels associated with a given religious tradition or context.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf3f07c08190a402e8341c1f38cc |
completed | March 1, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69a4bb67d52c8190815d6356b79d6ed5 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.