Triple
T1201763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krasnodar Krai |
E25796
|
entity |
| Predicate | hasResortCity |
P10436
|
FINISHED |
| Object |
Tuapse
Tuapse is a Black Sea port town in southern Russia known as a seaside resort and industrial center within Krasnodar Krai.
|
E195806
|
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: Tuapse | Statement: [Krasnodar Krai, hasResortCity, Tuapse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tuapse Context triple: [Krasnodar Krai, hasResortCity, Tuapse]
-
A.
Severodvinsk
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
-
B.
Murmansk
Murmansk is a major Arctic port city in northwestern Russia, known for its ice-free harbor and strategic military and shipping importance.
-
C.
Gelendzhik
Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
-
D.
Arkhangelsk
Arkhangelsk is a historic port city in northern Russia on the White Sea, long serving as a key maritime gateway and administrative center of the surrounding region.
-
E.
Kerch
Kerch is a historic port city in eastern Crimea, strategically located on the Kerch Strait linking the Black Sea and the Sea of Azov.
- 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: Tuapse Triple: [Krasnodar Krai, hasResortCity, Tuapse]
Generated description
Tuapse is a Black Sea port town in southern Russia known as a seaside resort and industrial center within Krasnodar Krai.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tuapse Target entity description: Tuapse is a Black Sea port town in southern Russia known as a seaside resort and industrial center within Krasnodar Krai.
-
A.
Severodvinsk
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
-
B.
Murmansk
Murmansk is a major Arctic port city in northwestern Russia, known for its ice-free harbor and strategic military and shipping importance.
-
C.
Gelendzhik
Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
-
D.
Arkhangelsk
Arkhangelsk is a historic port city in northern Russia on the White Sea, long serving as a key maritime gateway and administrative center of the surrounding region.
-
E.
Kerch
Kerch is a historic port city in eastern Crimea, strategically located on the Kerch Strait linking the Black Sea and the Sea of Azov.
- 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_69a4bf15423481909cb3e661e58d3d94 |
completed | March 1, 2026, 10:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada0b77f008190893627daee29c441 |
completed | March 8, 2026, 4:15 p.m. |
| NEDg | Description generation | batch_69ada1a0510481908ed8c36c9ae9a1a0 |
completed | March 8, 2026, 4:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ada26343988190bd067ca97186eb96 |
completed | March 8, 2026, 4:22 p.m. |
Created at: March 1, 2026, 7:46 p.m.