Triple
T33937982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | المدرسة النحوية البصرية |
E870085
|
entity |
| Predicate | تُدرَس_اليوم_ضمن |
P13197
|
FINISHED |
| Object |
تاريخ النحو العربي
تاريخ النحو العربي هو حقل دراسي يبحث في نشأة علم النحو وتطوره ومدارسه واتجاهاته عبر العصور في العالم العربي والإسلامي.
|
E2076182
|
NE FINISHED |
How this triple was built (3 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: تاريخ النحو العربي | Statement: [المدرسة النحوية البصرية, تُدرَس_اليوم_ضمن, تاريخ النحو العربي]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: تاريخ النحو العربي Triple: [المدرسة النحوية البصرية, تُدرَس_اليوم_ضمن, تاريخ النحو العربي]
Generated description
تاريخ النحو العربي هو حقل دراسي يبحث في نشأة علم النحو وتطوره ومدارسه واتجاهاته عبر العصور في العالم العربي والإسلامي.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تُدرَس_اليوم_ضمن Context triple: [المدرسة النحوية البصرية, تُدرَس_اليوم_ضمن, تاريخ النحو العربي]
-
A.
widelyStudiedIn
Indicates that something has been extensively researched, analyzed, or examined within a particular field, domain, or context.
-
B.
teachingUnit
Indicates that one entity functions as an instructional or educational unit used for teaching another entity.
-
C.
modernDisciplineStudying
Indicates that a contemporary academic or scientific discipline is engaged in the systematic study or investigation of a given subject or phenomenon.
-
D.
schoolSubjectContext
Indicates that an entity is being considered specifically in the context of a school subject or academic discipline.
-
E.
isTaughtAs
chosen
Indicates that something is presented or delivered as instructional content, typically within an educational or training context.
- F. None of above.
Provenance (6 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_69f3499a59788190bff762a891471b31 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3689d317b481909288a7249af8e9dd |
completed | June 20, 2026, 12:38 p.m. |
| NEDg | Description generation | batch_6a368d972f4c81909b4e5e4bd034b264 |
completed | June 20, 2026, 12:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a368e2093b88190a09398f5e3fa664f |
completed | June 20, 2026, 12:57 p.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:49 a.m.