Triple
T10114223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NRSVue with Apocrypha |
E218315
|
entity |
| Predicate | containsAdditionalBooks |
P5478
|
FINISHED |
| Object | Apocryphal books |
—
|
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: Apocryphal books | Statement: [NRSVue with Apocrypha, containsAdditionalBooks, Apocryphal books]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsAdditionalBooks Context triple: [NRSVue with Apocrypha, containsAdditionalBooks, Apocryphal books]
-
A.
containsBook
chosen
Indicates that one entity (typically a container or collection) includes a specific book as part of its contents.
-
B.
hasCompanionBook
Indicates that one entity (typically a primary work) is associated with another entity that serves as its companion book, providing supplementary or related content.
-
C.
hasBook
Indicates that an entity possesses, owns, or is associated with a particular book.
-
D.
book1Contains
Indicates that one book includes, encloses, or has as part of its content another specified element or section.
-
E.
alsoReadBy
Indicates that an item (such as a document, article, or book) has been read by another user or entity in addition to the primary one under consideration.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd15ffcd48190825800611aab2aab |
completed | April 2, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9ed7e48190aa132ef8a69b49f9 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:04 p.m.