Triple
T19074419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gospel of the Hebrews |
E466867
|
entity |
| Predicate | hasFragmentCount |
P20105
|
FINISHED |
| Object | approximately seven major fragments |
—
|
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: approximately seven major fragments | Statement: [Gospel of the Hebrews, hasFragmentCount, approximately seven major fragments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFragmentCount Context triple: [Gospel of the Hebrews, hasFragmentCount, approximately seven major fragments]
-
A.
hasFragments
Indicates that an entity is composed of, contains, or is associated with one or more smaller constituent parts or pieces.
-
B.
numberOfFragmentsApprox
chosen
Indicates an approximate count of how many fragments or pieces are associated with the subject.
-
C.
hasComponentCount
Indicates that an entity is associated with a specific number of components it contains or comprises.
-
D.
canBeFragmented
Indicates that something is capable of being broken, divided, or split into smaller parts or fragments.
-
E.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e2e2ccbc8190bf5a2da915c81a03 |
completed | April 20, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e4b99f602881909eeb9c780597e0e6 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:04 p.m.