Triple
T19381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Catholicism |
E384
|
entity |
| Predicate | hasOldTestamentCanon |
P977
|
FINISHED |
| Object | includes Deuterocanonical books |
—
|
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: includes Deuterocanonical books | Statement: [Roman Catholicism, hasOldTestamentCanon, includes Deuterocanonical books]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOldTestamentCanon Context triple: [Roman Catholicism, hasOldTestamentCanon, includes Deuterocanonical books]
-
A.
hasLanguageOfScripture
Indicates that an entity’s scriptural or sacred texts are written or expressed in a specified language.
-
B.
hasSacredText
Indicates that an entity possesses or is associated with a particular sacred or religious text.
-
C.
inCanonOf
chosen
Indicates that one entity is officially recognized as part of the established canon or authoritative body of works associated with another entity.
-
D.
hasLegacy
Indicates that an entity leaves behind a lasting impact, influence, or inheritance that continues to exist or be recognized over time.
-
E.
hasRiteOrTradition
Indicates that an entity is associated with, practices, or observes a particular rite, ritual, or tradition.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a246cbca108190a92478df126d9bf8 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a2464f61648190ac690044be194972 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.