Triple
T12082631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سيف الإسلام معمر القذافي |
E287717
|
entity |
| Predicate | المؤهل_العلمي |
P6
|
FINISHED |
| Object | دراسة في الهندسة |
—
|
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: دراسة في الهندسة | Statement: [سيف الإسلام معمر القذافي, المؤهل_العلمي, دراسة في الهندسة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: المؤهل_العلمي Context triple: [سيف الإسلام معمر القذافي, المؤهل_العلمي, دراسة في الهندسة]
-
A.
academicDegree
chosen
Indicates that an entity holds or has been awarded a specific academic degree.
-
B.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
C.
educationField
Indicates the academic or professional discipline in which an entity has been educated or trained.
-
D.
educationStatus
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
-
E.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9178ad99c8190a54777b9bbe998bc |
completed | April 10, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69d915000454819089fee00022055599 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:48 p.m.