Triple
T28656751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minuscule 565 |
E725353
|
entity |
| Predicate | hasSectionNumbers |
P1632
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Minuscule 565, hasSectionNumbers, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionNumbers Context triple: [Minuscule 565, hasSectionNumbers, yes]
-
A.
isSectionNumber
Indicates that one entity is the section number identifier associated with another entity, typically within a structured document or text.
-
B.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
-
C.
hasSectionCount
chosen
Indicates that an entity is associated with a specific number of sections it contains or comprises.
-
D.
hasCategoryNumbering
Indicates that an entity is assigned or associated with a specific category-based numbering or index within a classification system.
-
E.
hasChapterStructure
Indicates that one entity is organized into chapters or contains a defined chapter-based structure in relation to another entity.
- 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_69f01d84f5f0819087ab5e6143b14ed7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fda5003cdc8190a558501271389912 |
completed | May 8, 2026, 8:55 a.m. |
| PD | Predicate disambiguation | batch_69fda05bfc2c819096821a5300e9bb24 |
completed | May 8, 2026, 8:35 a.m. |
Created at: April 28, 2026, 4:55 a.m.