Triple
T29586689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book VI: Sanctions in the Church |
E754038
|
entity |
| Predicate | updatedSubjectMatter |
P450
|
FINISHED |
| Object | offences against the sacraments |
—
|
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: offences against the sacraments | Statement: [Book VI: Sanctions in the Church, updatedSubjectMatter, offences against the sacraments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: updatedSubjectMatter Context triple: [Book VI: Sanctions in the Church, updatedSubjectMatter, offences against the sacraments]
-
A.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
B.
subjectMatterScope
Indicates the thematic or topical domain that an action, statement, or resource pertains to or falls within.
-
C.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
D.
subjectGroup
Indicates that an entity functions as a group or collection that the subject belongs to or is categorized under.
-
E.
teachingSubject
Indicates that an entity is engaged in teaching or instructing another entity in a particular subject or field of knowledge.
- 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f66d7dfb948190b35070cef785d6b8 |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 6:11 p.m.