Triple
T22658067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | يوسف والي |
E559283
|
entity |
| Predicate | مجال الاهتمام |
P74482
|
FINISHED |
| Object | الزراعة |
—
|
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: الزراعة | Statement: [يوسف والي, مجال الاهتمام, الزراعة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: مجال الاهتمام Context triple: [يوسف والي, مجال الاهتمام, الزراعة]
-
A.
disciplinaryFocus
Indicates the primary academic or professional field, subject area, or discipline that something is centered on or concerned with.
-
B.
fieldOfSignificance
Indicates that something holds particular importance, relevance, or impact within a specified domain, context, or area of interest.
-
C.
regionOfAcademicInterest
chosen
Indicates that an entity has a particular academic field or subject area as its focus of interest or study.
-
D.
subjectInterest
Indicates that the subject has an interest in, or is concerned with, the object.
-
E.
primaryInterest
Indicates that one entity is the main or most significant focus of attention, concern, or engagement for another entity.
- 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_69e245489dd88190b1f674acf61c8769 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1765d10588190b4574f3e64617cd4 |
completed | April 29, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69ee6294c4c08190b7e4829f4b9af24b |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:07 p.m.