Triple
T2297439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Epistle to the Thessalonians |
E51649
|
entity |
| Predicate | biblicalChapterCount |
P2946
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Second Epistle to the Thessalonians, biblicalChapterCount, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: biblicalChapterCount Context triple: [Second Epistle to the Thessalonians, biblicalChapterCount, 3]
-
A.
numberOfBiblicalBooks
Indicates the total count of books contained in a specified version or canon of the Bible.
-
B.
numberOfChapters
chosen
Indicates the total count of chapters associated with a given entity.
-
C.
mostVersesChapter
Indicates that a chapter has the highest number of verses compared to all other chapters within the same collection or text.
-
D.
chapterNumberInLuke
Indicates the chapter number that a referenced passage or event appears in within the Book of Luke.
-
E.
bookNumberInNewTestament
Indicates the numerical position a specific book occupies within the sequence of books in the New Testament.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcd0e42248190ada33b84d75caa64 |
completed | March 7, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69abc589295c819092989820c2b4e9d8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.