Triple
T28977326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | بنينة |
E734447
|
entity |
| Predicate | تقع_في_المحافظة_أو_المديرية |
P115028
|
FINISHED |
| Object | محافظة بنغازي |
—
|
NE NERFINISHED |
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: محافظة بنغازي | Statement: [بنينة, تقع_في_المحافظة_أو_المديرية, محافظة بنغازي]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تقع_في_المحافظة_أو_المديرية Context triple: [بنينة, تقع_في_المحافظة_أو_المديرية, محافظة بنغازي]
-
A.
isLocatedInGovernorate
chosen
Indicates that an entity is situated within the administrative area of a specific governorate.
-
B.
locatedInCountySeatOfCounty
Indicates that one entity is located in the county seat city or town of the specified county.
-
C.
locatedInGovernorateCapitalRegion
Indicates that an entity is situated within the capital region of a governorate.
-
D.
situéeDansLeDépartement
Indicates that one entity is located within the administrative boundaries of a specific department.
-
E.
locatedInMunicipalAssociation
Indicates that an entity (typically a municipality or locality) is situated within and belongs administratively to a specific municipal association.
- 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_69f05b0d1e7c819092baab93d3fe277e |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65ee1cc508190bc979963e3589271 |
completed | May 2, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 9:09 a.m.