Triple
T9960923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyova |
E195564
|
entity |
| Predicate | hasNameVariant |
P457
|
FINISHED |
| Object |
Lyóva
Lyóva is a given name, typically a variant or transliteration of the name Lyova used in certain Slavic or Eastern European contexts.
|
E831911
|
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: Lyóva | Statement: [Lyova, hasNameVariant, Lyóva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lyóva Context triple: [Lyova, hasNameVariant, Lyóva]
-
A.
Liozna
Liozna is a small settlement in present-day Belarus historically known as the birthplace of the artist Marc Chagall.
-
B.
Devnya
Devnya is an industrial town in northeastern Bulgaria known for its large chemical and cement plants and its location near the Black Sea port city of Varna.
-
C.
Nydri
Nydri is a popular coastal village and tourist resort on the Greek island of Lefkada, known for its scenic harbor, nearby islets, and vibrant waterfront.
-
D.
Medveditsa
Medveditsa is a river in southwestern Russia that flows through the Volgograd and Saratov regions before joining the Don River.
-
E.
Vishkanya
Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
- 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: Lyóva Triple: [Lyova, hasNameVariant, Lyóva]
Generated description
Lyóva is a given name, typically a variant or transliteration of the name Lyova used in certain Slavic or Eastern European contexts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lyóva Target entity description: Lyóva is a given name, typically a variant or transliteration of the name Lyova used in certain Slavic or Eastern European contexts.
-
A.
Liozna
Liozna is a small settlement in present-day Belarus historically known as the birthplace of the artist Marc Chagall.
-
B.
Devnya
Devnya is an industrial town in northeastern Bulgaria known for its large chemical and cement plants and its location near the Black Sea port city of Varna.
-
C.
Nydri
Nydri is a popular coastal village and tourist resort on the Greek island of Lefkada, known for its scenic harbor, nearby islets, and vibrant waterfront.
-
D.
Medveditsa
Medveditsa is a river in southwestern Russia that flows through the Volgograd and Saratov regions before joining the Don River.
-
E.
Vishkanya
Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb6d219c48190b2084b0eb07ae125 |
completed | April 2, 2026, 12:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23d904bbc8190ac0b28600ed2e709 |
completed | April 5, 2026, 10:46 a.m. |
| NEDg | Description generation | batch_69d23fa1e3288190b755b3966178ad52 |
completed | April 5, 2026, 10:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d24077720c81909a43ff56627095a1 |
completed | April 5, 2026, 10:59 a.m. |
Created at: March 30, 2026, 8:47 p.m.