Triple
T13266567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shebin El Qanater |
E315939
|
entity |
| Predicate | governmentCountryType |
P66248
|
FINISHED |
| Object | unitary semi-presidential republic |
—
|
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: unitary semi-presidential republic | Statement: [Shebin El Qanater, governmentCountryType, unitary semi-presidential republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governmentCountryType Context triple: [Shebin El Qanater, governmentCountryType, unitary semi-presidential republic]
-
A.
countryType
Indicates the classification or category of a country based on a specified typology (e.g., political, economic, or geographic type).
-
B.
hasGovernmentTypeCountry
chosen
Indicates that a country possesses or is characterized by a particular form or type of government.
-
C.
sovereignStateType
Indicates the classification of a sovereign state according to its constitutional or political system (e.g., republic, monarchy, federation).
-
D.
countryDeJure
Indicates that one entity is the legally recognized (de jure) country having sovereignty or authority over another entity.
-
E.
collectionCountry
Indicates the country in which an item, specimen, or data was collected.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f60911081909fa346a054f76c9f |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:25 p.m.