Triple
T5260587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Ai |
E118812
|
entity |
| Predicate | scripturalChapters |
P62595
|
FINISHED |
| Object | Joshua 7 |
—
|
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: Joshua 7 | Statement: [Battle of Ai, scripturalChapters, Joshua 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scripturalChapters Context triple: [Battle of Ai, scripturalChapters, Joshua 7]
-
A.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
B.
chapterNumber
Indicates the specific ordinal position a chapter occupies within a larger ordered work, such as a book or document.
-
C.
mostVersesChapter
Indicates that a chapter has the highest number of verses compared to all other chapters within the same collection or text.
-
D.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
E.
scripturalSection
Indicates a relationship where one text or passage is a specific section or subdivision within a larger scriptural work.
- F. None of above. chosen
Provenance (4 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bcf026c8190881b6e14b962a3c9 |
completed | March 20, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69bd77c55224819096c0bcfcfae79bd3 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd7bcabe58819096255672664513b1 |
completed | March 20, 2026, 4:54 p.m. |
Created at: March 20, 2026, 1:50 p.m.