Triple
T2269290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESV Reader’s Bible |
E50619
|
entity |
| Predicate | textDivision |
P22618
|
FINISHED |
| Object | canonical order of biblical 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: canonical order of biblical books | Statement: [ESV Reader’s Bible, textDivision, canonical order of biblical books]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textDivision Context triple: [ESV Reader’s Bible, textDivision, canonical order of biblical books]
-
A.
textFragment
Indicates that one piece of text is a constituent part or segment of a larger text.
-
B.
textualStructure
chosen
Indicates how parts of a text are organized and related to each other within its overall structure.
-
C.
panelDivision
Indicates a relationship where a larger panel or board is divided into smaller sections or segments.
-
D.
tabletContentDivision
Indicates how the content displayed on a tablet device is partitioned or divided into distinct sections or regions.
-
E.
textType
Indicates the classification of a text according to its type, format, or genre.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc39c6ff0819081a07696f1c29990 |
completed | March 7, 2026, 6:20 a.m. |
| PD | Predicate disambiguation | batch_69abbdb7719081909143efa8f48df4e4 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.