Triple

T176816
Position Surface form Disambiguated ID Type / Status
Subject Albanian language E3590 entity
Predicate hasMajorDialect P1254 FINISHED
Object Tosk
Tosk is the southern variety of Albanian that forms the basis of the standard Albanian language.
 E22786 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: Tosk | Statement: [Albanian language, hasMajorDialect, Tosk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tosk
Context triple: [Albanian language, hasMajorDialect, Tosk]
  • A. Usk
    Usk is a small historic town in Monmouthshire, southeast Wales, known for its medieval castle and picturesque setting on the River Usk.
  • B. Marić
    Marić is the Serbian family name of Mileva Marić, a pioneering physicist and mathematician known for her association with Albert Einstein.
  • C. Tverya
    Tverya is the Hebrew name for Tiberias, an ancient city in northern Israel on the western shore of the Sea of Galilee known for its religious significance and hot springs.
  • D. Gweru
    Gweru is a central Zimbabwean city that serves as the capital of the Midlands Province and an important commercial and transportation hub.
  • E. Sicel
    Sicel was an ancient Indo-European language once spoken by the Sicel people in eastern Sicily before the dominance of Latin and Greek in the region.
  • 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: Tosk
Triple: [Albanian language, hasMajorDialect, Tosk]
Generated description
Tosk is the southern variety of Albanian that forms the basis of the standard Albanian language.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tosk
Target entity description: Tosk is the southern variety of Albanian that forms the basis of the standard Albanian language.
  • A. Usk
    Usk is a small historic town in Monmouthshire, southeast Wales, known for its medieval castle and picturesque setting on the River Usk.
  • B. Marić
    Marić is the Serbian family name of Mileva Marić, a pioneering physicist and mathematician known for her association with Albert Einstein.
  • C. Tverya
    Tverya is the Hebrew name for Tiberias, an ancient city in northern Israel on the western shore of the Sea of Galilee known for its religious significance and hot springs.
  • D. Gweru
    Gweru is a central Zimbabwean city that serves as the capital of the Midlands Province and an important commercial and transportation hub.
  • E. Sicel
    Sicel was an ancient Indo-European language once spoken by the Sicel people in eastern Sicily before the dominance of Latin and Greek in the region.
  • 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_69a25374990081909766d30c79a18e0e completed Feb. 28, 2026, 2:31 a.m.
NER Named-entity recognition batch_69a258fd278481908ad4498e03f38e2f completed Feb. 28, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2f0b4f1708190b766e1d9b43038ed completed Feb. 28, 2026, 1:42 p.m.
NEDg Description generation batch_69a2f12e5f548190a0fb3ca1cb059be1 completed Feb. 28, 2026, 1:44 p.m.
NED2 Entity disambiguation (via description) batch_69a2f39599b08190be95c9ec634c5745 completed Feb. 28, 2026, 1:54 p.m.
Created at: Feb. 28, 2026, 2:39 a.m.