Triple
T1201758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krasnodar Krai |
E25796
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Gelendzhik
Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
|
E166972
|
NE FINISHED |
How this triple was built (4 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: Gelendzhik | Statement: [Krasnodar Krai, hasCity, Gelendzhik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gelendzhik Context triple: [Krasnodar Krai, hasCity, Gelendzhik]
-
A.
Novorossiysk
Novorossiysk is a major port city on Russia’s Black Sea coast that serves as an important naval and commercial hub.
-
B.
Yevpatoria
Yevpatoria is a historic resort and port city on the western coast of Crimea, known for its beaches, therapeutic mud treatments, and diverse cultural heritage.
-
C.
Taganrog
Taganrog is a port city in southwestern Russia on the northern coast of the Sea of Azov, known for its maritime trade and as the birthplace of writer Anton Chekhov.
-
D.
Berdyansk
Berdyansk is a port city in southeastern Ukraine on the northern coast of the Sea of Azov, known for its maritime trade, beaches, and resort facilities.
-
E.
Severodvinsk
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gelendzhik Triple: [Krasnodar Krai, hasCity, Gelendzhik]
Generated description
Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gelendzhik Target entity description: Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
-
A.
Novorossiysk
Novorossiysk is a major port city on Russia’s Black Sea coast that serves as an important naval and commercial hub.
-
B.
Yevpatoria
Yevpatoria is a historic resort and port city on the western coast of Crimea, known for its beaches, therapeutic mud treatments, and diverse cultural heritage.
-
C.
Taganrog
Taganrog is a port city in southwestern Russia on the northern coast of the Sea of Azov, known for its maritime trade and as the birthplace of writer Anton Chekhov.
-
D.
Berdyansk
Berdyansk is a port city in southeastern Ukraine on the northern coast of the Sea of Azov, known for its maritime trade, beaches, and resort facilities.
-
E.
Severodvinsk
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
- F. None of above. chosen
Provenance (5 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd9fece4819089a6a2d61e61fa2e |
completed | March 1, 2026, 10:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0e5dd8148190a209257ee29969dd |
completed | March 8, 2026, 5:51 a.m. |
| NEDg | Description generation | batch_69ad0ed1fb608190a9295808e144d0fb |
completed | March 8, 2026, 5:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad0f90cdec81908a981e12184cdd75 |
completed | March 8, 2026, 5:56 a.m. |
Created at: March 1, 2026, 7:46 p.m.