Triple
T20845466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berehove |
E513212
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object |
Берегове
Берегове — це місто в Закарпатській області України, відоме своєю угорською громадою, виноробними традиціями та термальними джерелами.
|
E1453382
|
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: Берегове | Statement: [Berehove, alternativeName, Берегове]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Берегове Context triple: [Berehove, alternativeName, Берегове]
-
A.
Rokovoj Bereg
Rokovoj Bereg is a climactic musical track from the Metal Gear Solid 3: Snake Eater soundtrack, associated with one of the game's most pivotal and emotional confrontations.
-
B.
Barsheni
Barsheni is a small Himalayan village in Himachal Pradesh, India, serving as a popular base for treks to places like Kheerganga and Tosh in the Parvati Valley.
-
C.
Livoberezhna
Livoberezhna is a metro station on the Kyiv Metro system, serving the left-bank area of Ukraine’s capital city.
-
D.
Tribeni
Tribeni is a town in West Bengal, India, historically known as a sacred confluence point of rivers and an important riverside settlement.
-
E.
Morsko
Morsko is a village in southern Poland known for its picturesque setting in the Kraków-Częstochowa Upland and its historic castle ruins.
- 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: Берегове Triple: [Berehove, alternativeName, Берегове]
Generated description
Берегове — це місто в Закарпатській області України, відоме своєю угорською громадою, виноробними традиціями та термальними джерелами.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Берегове Target entity description: Берегове — це місто в Закарпатській області України, відоме своєю угорською громадою, виноробними традиціями та термальними джерелами.
-
A.
Rokovoj Bereg
Rokovoj Bereg is a climactic musical track from the Metal Gear Solid 3: Snake Eater soundtrack, associated with one of the game's most pivotal and emotional confrontations.
-
B.
Barsheni
Barsheni is a small Himalayan village in Himachal Pradesh, India, serving as a popular base for treks to places like Kheerganga and Tosh in the Parvati Valley.
-
C.
Livoberezhna
Livoberezhna is a metro station on the Kyiv Metro system, serving the left-bank area of Ukraine’s capital city.
-
D.
Tribeni
Tribeni is a town in West Bengal, India, historically known as a sacred confluence point of rivers and an important riverside settlement.
-
E.
Morsko
Morsko is a village in southern Poland known for its picturesque setting in the Kraków-Częstochowa Upland and its historic castle ruins.
- 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c34ec254819082610264c7af20c8 |
completed | April 21, 2026, 12:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a090b03b5588190a98681307f32946f |
completed | May 17, 2026, 12:25 a.m. |
| NEDg | Description generation | batch_6a090b872f58819087803faf1293f1b7 |
completed | May 17, 2026, 12:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a090c57aef48190978b5fe94dd4feab |
completed | May 17, 2026, 12:31 a.m. |
Created at: April 16, 2026, 12:43 p.m.