Triple
T33457454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ابن جني |
E856815
|
entity |
| Predicate | موضوع كتاب المحتسب |
P177620
|
FINISHED |
| Object | توجيه القراءات الشاذة |
—
|
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: توجيه القراءات الشاذة | Statement: [ابن جني, موضوع كتاب المحتسب, توجيه القراءات الشاذة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: موضوع كتاب المحتسب Context triple: [ابن جني, موضوع كتاب المحتسب, توجيه القراءات الشاذة]
-
A.
موضوع كتاب سر صناعة الإعراب
Indicates that the subject or topic under discussion is the book "Sir Ṣināʿat al-Iʿrāb" (The Secret of the Craft of Parsing).
-
B.
book5Title
Indicates the title assigned to the book identified as "book5."
-
C.
book1Contains
Indicates that one book includes, encloses, or has as part of its content another specified element or section.
-
D.
عدد الحروف
Indicates the relationship that specifies the number of letters contained in a given word or text.
-
E.
عدد السجدات
Indicates the number of prostrations performed in a given prayer or worship context.
- 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_69f3497281a08190b4705de0b5f26ba7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7009d39508190af7301f824615e88 |
completed | May 3, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
| PDg | Predicate description generation | batch_69f6ffb7554881908993d6d2ffbcf8f5 |
completed | May 3, 2026, 7:56 a.m. |
Created at: May 1, 2026, 1:37 a.m.