Triple
T34029120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melk Abbey Chronicle |
E872593
|
entity |
| Predicate | religiousAffiliationOfAuthors |
P19416
|
FINISHED |
| Object | Benedictine monks |
—
|
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: Benedictine monks | Statement: [Melk Abbey Chronicle, religiousAffiliationOfAuthors, Benedictine monks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousAffiliationOfAuthors Context triple: [Melk Abbey Chronicle, religiousAffiliationOfAuthors, Benedictine monks]
-
A.
authorsReligion
chosen
Indicates the religious affiliation or belief system associated with an author.
-
B.
creatorReligiousAffiliation
Indicates the religious affiliation or tradition with which a creator is associated.
-
C.
hasAuthorTheologicalAffiliation
Indicates that an author is associated with a particular theological tradition, denomination, or belief system.
-
D.
associatedReligionInTexts
Indicates that a particular religion is mentioned or linked in written texts in connection with the given entity.
-
E.
associatedReligionText
Indicates that there is a textual work (such as a scripture or religious document) that is specifically associated with, or pertains to, a given religion.
- 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_69f349a2527c81909a7cd4bda94d70ad |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff59b33a38819086cc9aa19b81748b |
completed | May 9, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69ff587758f88190a39c2164341dc554 |
completed | May 9, 2026, 3:53 p.m. |
Created at: May 1, 2026, 1:51 a.m.