Triple
T33264921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | False Folio |
E851617
|
entity |
| Predicate | hasScholarlyTerm |
P63299
|
FINISHED |
| Object | Pavier quartos |
—
|
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: Pavier quartos | Statement: [False Folio, hasScholarlyTerm, Pavier quartos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScholarlyTerm Context triple: [False Folio, hasScholarlyTerm, Pavier quartos]
-
A.
isScholarly
Indicates that an entity exhibits characteristics of academic rigor, research-based inquiry, and adherence to scholarly standards or conventions.
-
B.
hasModernScholarlyTerm
chosen
Indicates that there exists a contemporary academic or scholarly term that corresponds to or designates the given entity or concept.
-
C.
isScholarlyDistinction
Indicates that something constitutes a formal academic honor, award, or special recognition conferred for scholarly achievement or excellence.
-
D.
hasScholarlyReception
Indicates that a work has been the subject of scholarly analysis, discussion, or evaluation in academic or research contexts.
-
E.
scholarlyUse
Indicates that something is used for academic, educational, or research-related purposes.
- 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_69f349642dac81908a37ffcc3b976a55 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: May 1, 2026, 1:32 a.m.