Triple
T34954251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libri tres adversus Simoniacos |
E1008084
|
entity |
| Predicate | religiousDisciplineAddressed |
P47348
|
FINISHED |
| Object | canon law |
—
|
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: canon law | Statement: [Libri tres adversus Simoniacos, religiousDisciplineAddressed, canon law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousDisciplineAddressed Context triple: [Libri tres adversus Simoniacos, religiousDisciplineAddressed, canon law]
-
A.
religiousTopicAddressed
chosen
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
-
B.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
C.
religiousEnvironment
Indicates the religious context, atmosphere, or setting in which an entity exists or an action takes place.
-
D.
religiousSpectrum
Indicates a relationship that places entities along a range or continuum of religious belief, practice, or affiliation.
-
E.
religiousFoundation
Indicates that an entity was established, created, or founded by a religious organization, authority, 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff8cecbf048190860b9f72b8753f5c |
completed | May 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69ff8c4c39dc8190b5bf35adc1bae7c6 |
completed | May 9, 2026, 7:34 p.m. |
Created at: May 3, 2026, 4 p.m.