Triple
T25127922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Orthodox Theology, University of Bucharest |
E629443
|
entity |
| Predicate | hasReligiousProfile |
P27703
|
FINISHED |
| Object | confessional |
—
|
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: confessional | Statement: [Faculty of Orthodox Theology, University of Bucharest, hasReligiousProfile, confessional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousProfile Context triple: [Faculty of Orthodox Theology, University of Bucharest, hasReligiousProfile, confessional]
-
A.
hasReligious
Indicates that an entity is associated with, practices, or adheres to a particular religion or religious affiliation.
-
B.
hasReligiousType
Indicates that an entity is associated with or classified under a particular religion or religious category.
-
C.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
D.
hasReligiousCharacter
chosen
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
-
E.
hasReligiousSelection
Indicates that an entity is chosen, classified, or filtered based on religious criteria or affiliation.
- 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_69e2ff3288048190bd82c3b7f7bd0e62 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 18, 2026, 6:28 a.m.