Triple
T37834975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upland Hungary |
E943312
|
entity |
| Predicate | religiouslyDiverseWith |
P42376
|
FINISHED |
| Object | Roman Catholics |
—
|
NE NERFINISHED |
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 Catholics | Statement: [Upland Hungary, religiouslyDiverseWith, Roman Catholics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiouslyDiverseWith Context triple: [Upland Hungary, religiouslyDiverseWith, Roman Catholics]
-
A.
religionDiversity
chosen
Indicates the degree to which multiple distinct religions are present and represented within a given context or group.
-
B.
isMultiReligious
Indicates that an entity is associated with or practices multiple religions rather than adhering to just one.
-
C.
ethnicReligionMix
Indicates a relationship where a group or context involves a combined or overlapping presence of specific ethnic identities and religious affiliations.
-
D.
religiousGroupsPresent
Indicates that one or more religious groups are present or represented in a given context, location, or situation.
-
E.
ethnicOrReligiousGroup
Indicates that one entity is an ethnic or religious group to which the other entity belongs or with which it is associated.
- 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_69f76eea4c8c8190a335aed5955cf2db |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a00372ff0e48190b3ed91f9bae9da6c |
completed | May 10, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_6a00359c1b8481909c1e43df9f5a789a |
completed | May 10, 2026, 7:37 a.m. |
Created at: May 3, 2026, 4:19 p.m.