Triple
T34453364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre Cauchon |
E884434
|
entity |
| Predicate | canonLawSpecialization |
P179654
|
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: [Pierre Cauchon, canonLawSpecialization, canon law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canonLawSpecialization Context triple: [Pierre Cauchon, canonLawSpecialization, canon law]
-
A.
canonLawSubject
Indicates that an entity is the subject or topic governed, regulated, or addressed by a particular canon law or set of canonical legal norms.
-
B.
canonLawTraining
Indicates that one entity has provided or received training or education in canon law in relation to another entity.
-
C.
canonLawContribution
Indicates a contribution an entity makes to the development, interpretation, or application of canon law.
-
D.
canonLawContext
Indicates that something occurs within, is governed by, or is interpreted according to the norms and framework of canon law.
-
E.
canonLawJurisdiction
Indicates the scope or authority under which canon law applies to or governs a particular entity or matter.
- F. None of above. chosen
Provenance (4 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_69f349c607688190b553539d14901a35 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7238172748190b8cd340ad1f4ba80 |
completed | May 3, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69f72155c48881909bd40b9aa3febd5a |
completed | May 3, 2026, 10:20 a.m. |
| PDg | Predicate description generation | batch_69f72349f1108190b6a06758ab2f40bb |
completed | May 3, 2026, 10:28 a.m. |
Created at: May 1, 2026, 2 a.m.