Triple
T20058119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World War II era in Spain |
E499393
|
entity |
| Predicate | religionInPolitics |
P36791
|
FINISHED |
| Object | strong influence of Catholic Church |
—
|
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: strong influence of Catholic Church | Statement: [World War II era in Spain, religionInPolitics, strong influence of Catholic Church]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religionInPolitics Context triple: [World War II era in Spain, religionInPolitics, strong influence of Catholic Church]
-
A.
religionPolicy
Indicates the stance, rules, or approach an entity adopts toward religious beliefs, practices, or institutions.
-
B.
religiousPolicyOutcome
Indicates the consequences or effects that a particular religious policy has on individuals, groups, or society.
-
C.
religiousAffiliation
Indicates that one entity has a specified religious association, belief system, or denominational membership.
-
D.
subjectReligion
Indicates that the subject is associated with, practices, or adheres to a particular religion.
-
E.
religiousAttitude
chosen
Indicates an entity’s stance, disposition, or orientation toward religion or religious beliefs.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6637325908190aefc0e27e2ed5750 |
completed | April 20, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:38 p.m.