Triple

T12594910
Position Surface form Disambiguated ID Type / Status
Subject Taraškievica E300707 entity
Predicate alternativeName P39 FINISHED
Object Taraškevica
Taraškevica is a traditional orthographic standard of the Belarusian language, often contrasted with the later official spelling.
 E991784 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: Taraškevica | Statement: [Taraškievica, alternativeName, Taraškevica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Taraškevica
Context triple: [Taraškievica, alternativeName, Taraškevica]
  • A. Tlmače
    Tlmače is a small industrial town in western Slovakia known for its energy-related manufacturing and location along the Hron River.
  • B. Blšanka
    Blšanka is a small river in the Czech Republic that flows through the Ústí nad Labem and Karlovy Vary regions before joining the Ohře River.
  • C. Begunjščica
    Begunjščica is a prominent mountain peak in the Karawanks range of the Southern Limestone Alps in Slovenia, popular for hiking and skiing.
  • D. Plešnar
    Plešnar is a Slovenian surname most notably borne by the photographer Zora Plešnar.
  • E. Tisler
    Tisler is a small Norwegian island in the Hvaler archipelago, known for its coastal scenery and traditional seaside cottages.
  • 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: Taraškevica
Triple: [Taraškievica, alternativeName, Taraškevica]
Generated description
Taraškevica is a traditional orthographic standard of the Belarusian language, often contrasted with the later official spelling.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Taraškevica
Target entity description: Taraškevica is a traditional orthographic standard of the Belarusian language, often contrasted with the later official spelling.
  • A. Tlmače
    Tlmače is a small industrial town in western Slovakia known for its energy-related manufacturing and location along the Hron River.
  • B. Blšanka
    Blšanka is a small river in the Czech Republic that flows through the Ústí nad Labem and Karlovy Vary regions before joining the Ohře River.
  • C. Begunjščica
    Begunjščica is a prominent mountain peak in the Karawanks range of the Southern Limestone Alps in Slovenia, popular for hiking and skiing.
  • D. Plešnar
    Plešnar is a Slovenian surname most notably borne by the photographer Zora Plešnar.
  • E. Tisler
    Tisler is a small Norwegian island in the Hvaler archipelago, known for its coastal scenery and traditional seaside cottages.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954cde3c0819094e74413d6dcf548 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ec49af881908abb948567b82b74 completed May 2, 2026, 8:29 p.m.
NEDg Description generation batch_69f65faf33e0819092df07a5fa98cb73 completed May 2, 2026, 8:33 p.m.
NED2 Entity disambiguation (via description) batch_69f66036f520819098af75cd5578d573 completed May 2, 2026, 8:36 p.m.
Created at: April 9, 2026, 5:08 p.m.