Triple
T6092449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luke 22 |
E135799
|
entity |
| Predicate | hasChapterNumber |
P14913
|
FINISHED |
| Object | 22 |
—
|
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: 22 | Statement: [Luke 22, hasChapterNumber, 22]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapterNumber Context triple: [Luke 22, hasChapterNumber, 22]
-
A.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
B.
chapterNumber
chosen
Indicates the specific ordinal position a chapter occupies within a larger ordered work, such as a book or document.
-
C.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
D.
hadChapterOf
Indicates that an entity (such as a book or document) includes or contains a specific chapter as one of its parts.
-
E.
chapterOn
Indicates that one entity (typically a chapter) is about, discusses, or focuses on the subject represented by 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057ab7324819086d4708e6f9391c0 |
completed | March 22, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:12 p.m.