Triple
T34689916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bridey Murphy |
E890862
|
entity |
| Predicate | allegedReligion |
P186988
|
FINISHED |
| Object | Roman Catholicism |
—
|
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: Roman Catholicism | Statement: [Bridey Murphy, allegedReligion, Roman Catholicism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allegedReligion Context triple: [Bridey Murphy, allegedReligion, Roman Catholicism]
-
A.
ethnicReligion
Indicates that a religion is closely associated with a particular ethnic group, often tied to that group’s culture, ancestry, or identity.
-
B.
associatedReligionOrBelief
Indicates that an entity is connected to, identified with, or characterized by a particular religion or belief system.
-
C.
religiousCounterpart
Indicates that one entity serves as the religious equivalent or analogue of another entity within a different belief system or tradition.
-
D.
religionOrBelief
Indicates that one entity holds, practices, or is associated with a particular religion, faith, or belief system.
-
E.
bearerReligion
Indicates that a bearer (such as a person or entity) adheres to, practices, or is associated with a particular religion.
- 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_69f349db7ab8819086808e833f472871 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fb2e940d5c8190bceae77daf4ef512 |
completed | May 6, 2026, 12:05 p.m. |
| PD | Predicate disambiguation | batch_69f9fec70bd881909c658a3c5020318b |
completed | May 5, 2026, 2:29 p.m. |
| PDg | Predicate description generation | batch_69fb2e9309fc81909dfefd9020d6fbad |
completed | May 6, 2026, 12:05 p.m. |
Created at: May 1, 2026, 2:05 a.m.