Triple

T9461647
Position Surface form Disambiguated ID Type / Status
Subject Prasuni E228159 entity
Predicate hasDialect P4251 FINISHED
Object Wasi dialect
The Wasi dialect is a regional variety of the Prasuni language spoken by a subset of the Prasun people in Afghanistan’s Nuristan region.
 E800958 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: Wasi dialect | Statement: [Prasuni, hasDialect, Wasi dialect]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wasi dialect
Context triple: [Prasuni, hasDialect, Wasi dialect]
  • A. Razihi dialect
    The Razihi dialect is a highly distinctive and conservative Arabic variety spoken in parts of northwestern Yemen, noted for preserving many archaic linguistic features.
  • B. Barwar dialect
    The Barwar dialect is a regional variety of Assyrian Neo-Aramaic traditionally spoken by Assyrian communities from the Barwar region in northern Iraq.
  • C. Weda dialect
    The Weda dialect is a regional variety of the Sawai language spoken by communities in the Weda area of Halmahera in eastern Indonesia.
  • D. Takbanuaz dialect
    The Takbanuaz dialect is a regional variety of the Bunun language spoken by an indigenous Bunun subgroup in Taiwan.
  • E. Bajelani dialect
    The Bajelani dialect is a regional variety of the Gorani language spoken by Kurdish communities in parts of the Middle East.
  • 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: Wasi dialect
Triple: [Prasuni, hasDialect, Wasi dialect]
Generated description
The Wasi dialect is a regional variety of the Prasuni language spoken by a subset of the Prasun people in Afghanistan’s Nuristan region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wasi dialect
Target entity description: The Wasi dialect is a regional variety of the Prasuni language spoken by a subset of the Prasun people in Afghanistan’s Nuristan region.
  • A. Razihi dialect
    The Razihi dialect is a highly distinctive and conservative Arabic variety spoken in parts of northwestern Yemen, noted for preserving many archaic linguistic features.
  • B. Barwar dialect
    The Barwar dialect is a regional variety of Assyrian Neo-Aramaic traditionally spoken by Assyrian communities from the Barwar region in northern Iraq.
  • C. Weda dialect
    The Weda dialect is a regional variety of the Sawai language spoken by communities in the Weda area of Halmahera in eastern Indonesia.
  • D. Takbanuaz dialect
    The Takbanuaz dialect is a regional variety of the Bunun language spoken by an indigenous Bunun subgroup in Taiwan.
  • E. Bajelani dialect
    The Bajelani dialect is a regional variety of the Gorani language spoken by Kurdish communities in parts of the Middle East.
  • 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_69ca843b123881909b0e60028475d12d completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7fcc8b1881908aa6ee13ab195330 completed April 1, 2026, 8:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1229ec9448190bac9b7a38e030833 completed April 4, 2026, 2:39 p.m.
NEDg Description generation batch_69d1245db2e48190a56a797a681316d9 completed April 4, 2026, 2:46 p.m.
NED2 Entity disambiguation (via description) batch_69d124c2a48c819098a24dd2aac734e1 completed April 4, 2026, 2:48 p.m.
Created at: March 30, 2026, 7:52 p.m.