Triple
T3225653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Ash-Sharh |
E67614
|
entity |
| Predicate | chapterOrder |
P14913
|
FINISHED |
| Object | ninety-fourth chapter of the Quran |
—
|
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: ninety-fourth chapter of the Quran | Statement: [Surah Ash-Sharh, chapterOrder, ninety-fourth chapter of the Quran]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chapterOrder Context triple: [Surah Ash-Sharh, chapterOrder, ninety-fourth chapter of the Quran]
-
A.
chapterNumber
chosen
Indicates the specific ordinal position a chapter occupies within a larger ordered work, such as a book or document.
-
B.
chapterOn
Indicates that one entity (typically a chapter) is about, discusses, or focuses on the subject represented by another entity.
-
C.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
D.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
E.
chapterType
Indicates the specific kind or category of a chapter within a larger work or document.
- 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_69ad858c61888190a31196310d9b30b5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adae1c51a48190b4a395650528b5d8 |
completed | March 8, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0bb6c48190a0659c67d40ee37c |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:08 p.m.