Triple
T6517398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Cow |
E148299
|
entity |
| Predicate | hasPageRangeInMushaf |
P71347
|
FINISHED |
| Object | 2–49 |
—
|
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: 2–49 | Statement: [The Cow, hasPageRangeInMushaf, 2–49]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPageRangeInMushaf Context triple: [The Cow, hasPageRangeInMushaf, 2–49]
-
A.
positionInMushaf
Indicates the specific location or ordering of a text segment within the physical or canonical arrangement of the Mushaf (written Qur’an).
-
B.
hasJuzRange
Indicates that an entity (such as a text or passage) spans, is associated with, or falls within a specified range of Juz segments.
-
C.
hasVerseRange
Indicates a relationship where a text or passage is associated with a specific contiguous range of verses it spans.
-
D.
bookChapterRange
Indicates a relationship where a specified range of chapters within a book is identified or referenced as a contiguous segment.
-
E.
hasPageCountApprox
Indicates that an entity is associated with an approximate or estimated number of pages, rather than an exact page count.
- 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_69c687e68e748190baceb9298f32d3ed |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ac0ece2081909c14accef90efd7c |
completed | March 27, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69c68ab98c78819081743e614df04e1d |
completed | March 27, 2026, 1:48 p.m. |
| PDg | Predicate description generation | batch_69c69f362ee4819090e8fa48caef7d7d |
completed | March 27, 2026, 3:16 p.m. |
Created at: March 27, 2026, 1:44 p.m.