Triple
T4841689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marian devotions |
E108191
|
entity |
| Predicate | practitioner |
P37643
|
FINISHED |
| Object | individual believers |
—
|
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: individual believers | Statement: [Marian devotions, practitioner, individual believers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: practitioner Context triple: [Marian devotions, practitioner, individual believers]
-
A.
notablePractitioner
Indicates that an entity is a well-known or distinguished practitioner of a particular field, discipline, or activity.
-
B.
trainer
Indicates a relationship where one entity teaches, coaches, or prepares another entity to develop skills, knowledge, or performance in a particular domain.
-
C.
primaryPractitioners
chosen
Indicates the entities that are the main or most directly responsible practitioners of a given activity, field, or practice in relation to another entity.
-
D.
practicedMedicineIn
Indicates that a person engaged in the professional practice of medicine within a specified location or jurisdiction.
-
E.
practice
Indicates that an entity regularly performs an activity or skill, typically to improve proficiency or maintain competence.
- 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_69bd4409b264819085ab855f3eb5381a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e01872c81909607010c10538ad1 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2375a4819098e16acb982c8fab |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:25 p.m.