Triple
T17570781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berezhany |
E427929
|
entity |
| Predicate | hasEducationalInstitution |
P113
|
FINISHED |
| Object | Berezhany Agrotechnical Institute |
—
|
NE NERFINISHED |
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: Berezhany Agrotechnical Institute | Statement: [Berezhany, hasEducationalInstitution, Berezhany Agrotechnical Institute]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berezhany Agrotechnical Institute Context triple: [Berezhany, hasEducationalInstitution, Berezhany Agrotechnical Institute]
-
A.
Minsk Institute of Agriculture
The Minsk Institute of Agriculture was a higher education institution in Minsk specializing in agricultural sciences and training agronomists and related specialists in the Soviet era.
-
B.
Poltava State Agrarian University
Poltava State Agrarian University is a higher education institution in Poltava, Ukraine, specializing in agricultural sciences and related fields.
-
C.
Sumy National Agrarian University
Sumy National Agrarian University is a higher education institution in Sumy, Ukraine, specializing in agricultural sciences, veterinary medicine, and related fields.
-
D.
Research Institute of Agriculture of Crimea
The Research Institute of Agriculture of Crimea is a specialized scientific center focused on advancing agricultural research and technologies tailored to the climatic and soil conditions of the Crimean region.
-
E.
Nizhyn Gymnasium of Higher Sciences
Nizhyn Gymnasium of Higher Sciences was a prominent early 19th-century educational institution in Nizhyn, in the Russian Empire (now Ukraine), known for training many notable intellectuals, including writer Nikolai Gogol.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Berezhany Agrotechnical Institute Target entity description: Berezhany Agrotechnical Institute is a Ukrainian higher education institution specializing in agricultural and technical disciplines, located in the town of Berezhany.
-
A.
Minsk Institute of Agriculture
The Minsk Institute of Agriculture was a higher education institution in Minsk specializing in agricultural sciences and training agronomists and related specialists in the Soviet era.
-
B.
Poltava State Agrarian University
Poltava State Agrarian University is a higher education institution in Poltava, Ukraine, specializing in agricultural sciences and related fields.
-
C.
Sumy National Agrarian University
Sumy National Agrarian University is a higher education institution in Sumy, Ukraine, specializing in agricultural sciences, veterinary medicine, and related fields.
-
D.
Research Institute of Agriculture of Crimea
The Research Institute of Agriculture of Crimea is a specialized scientific center focused on advancing agricultural research and technologies tailored to the climatic and soil conditions of the Crimean region.
-
E.
Nizhyn Gymnasium of Higher Sciences
Nizhyn Gymnasium of Higher Sciences was a prominent early 19th-century educational institution in Nizhyn, in the Russian Empire (now Ukraine), known for training many notable intellectuals, including writer Nikolai Gogol.
- F. None of above. chosen
Provenance (2 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45930b0748190b55b95c523c47460 |
completed | April 19, 2026, 4:25 a.m. |
Created at: April 10, 2026, 5:50 a.m.