Triple
T7320917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sverdlovsk Oblast |
E168541
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Revda
Revda is an industrial town in Russia’s Ural region, known historically for its mining and metallurgical industries.
|
E657603
|
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: Revda | Statement: [Sverdlovsk Oblast, hasCity, Revda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Revda Context triple: [Sverdlovsk Oblast, hasCity, Revda]
-
A.
Logudoro
Logudoro is a historical-cultural region in northern Sardinia known for its distinctive Sardinian dialect, medieval heritage, and rural landscapes.
-
B.
Ginosa
Ginosa is a town and comune in the Apulia region of southern Italy, known for its historic center and proximity to the Ionian coast.
-
C.
Burano
Burano is a small, picturesque island in the Venetian Lagoon renowned for its brightly colored houses and traditional lace-making.
-
D.
Populonia
Populonia was an important ancient coastal city of Etruria, known for its maritime trade, metalworking, and strategic position on the Tyrrhenian Sea.
-
E.
Alushta
Alushta is a resort town on the southern coast of Crimea, known for its beaches, mild climate, and role as a popular Black Sea tourist destination.
- 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: Revda Triple: [Sverdlovsk Oblast, hasCity, Revda]
Generated description
Revda is an industrial town in Russia’s Ural region, known historically for its mining and metallurgical industries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Revda Target entity description: Revda is an industrial town in Russia’s Ural region, known historically for its mining and metallurgical industries.
-
A.
Logudoro
Logudoro is a historical-cultural region in northern Sardinia known for its distinctive Sardinian dialect, medieval heritage, and rural landscapes.
-
B.
Ginosa
Ginosa is a town and comune in the Apulia region of southern Italy, known for its historic center and proximity to the Ionian coast.
-
C.
Burano
Burano is a small, picturesque island in the Venetian Lagoon renowned for its brightly colored houses and traditional lace-making.
-
D.
Populonia
Populonia was an important ancient coastal city of Etruria, known for its maritime trade, metalworking, and strategic position on the Tyrrhenian Sea.
-
E.
Alushta
Alushta is a resort town on the southern coast of Crimea, known for its beaches, mild climate, and role as a popular Black Sea tourist destination.
- 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_69c68a5251508190ad68df4151cfeb04 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ef1ba58481909cfb5030b85f385a |
completed | March 27, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ef01ea8c819091cd4106039c121e |
completed | March 28, 2026, 3:08 p.m. |
| NEDg | Description generation | batch_69c7ef7f7b7c8190b3361cc01b2eefc0 |
completed | March 28, 2026, 3:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7f380dbe48190933e1eeff109185d |
completed | March 28, 2026, 3:28 p.m. |
Created at: March 27, 2026, 3:02 p.m.