Triple

T15873757
Position Surface form Disambiguated ID Type / Status
Subject རྫོང་ཁ E384893 entity
Predicate hasDialects P4251 FINISHED
Object Haa dialect
The Haa dialect is a regional variety of the Dzongkha language spoken primarily in Bhutan’s Haa Valley, distinguished by its unique phonological and lexical features.
 E1180961 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: Haa dialect | Statement: [རྫོང་ཁ, hasDialects, Haa dialect]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Haa dialect
Context triple: [རྫོང་ཁ, hasDialects, Haa dialect]
  • A. Harauti dialect
    The Harauti dialect is an Indo-Aryan variety spoken primarily in the Hadoti (Harauti) region of Rajasthan and neighboring areas of India.
  • B. Taai dialect
    The Taai dialect is a regional variety of the Saisiyat language spoken by the indigenous Saisiyat people of Taiwan.
  • C. Satawan dialect
    The Satawan dialect is a regional variety of the Mortlockese language spoken primarily on Satawan Atoll in the Federated States of Micronesia.
  • D. Hkaku dialect
    Hkaku dialect is a regional variety of the Jingpo language spoken by Jingpo communities in parts of Myanmar and neighboring areas.
  • E. Loinang dialect
    The Loinang dialect is a regional variety of the Saluan language spoken by communities in parts of Central Sulawesi, Indonesia.
  • 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: Haa dialect
Triple: [རྫོང་ཁ, hasDialects, Haa dialect]
Generated description
The Haa dialect is a regional variety of the Dzongkha language spoken primarily in Bhutan’s Haa Valley, distinguished by its unique phonological and lexical features.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Haa dialect
Target entity description: The Haa dialect is a regional variety of the Dzongkha language spoken primarily in Bhutan’s Haa Valley, distinguished by its unique phonological and lexical features.
  • A. Harauti dialect
    The Harauti dialect is an Indo-Aryan variety spoken primarily in the Hadoti (Harauti) region of Rajasthan and neighboring areas of India.
  • B. Taai dialect
    The Taai dialect is a regional variety of the Saisiyat language spoken by the indigenous Saisiyat people of Taiwan.
  • C. Satawan dialect
    The Satawan dialect is a regional variety of the Mortlockese language spoken primarily on Satawan Atoll in the Federated States of Micronesia.
  • D. Hkaku dialect
    Hkaku dialect is a regional variety of the Jingpo language spoken by Jingpo communities in parts of Myanmar and neighboring areas.
  • E. Loinang dialect
    The Loinang dialect is a regional variety of the Saluan language spoken by communities in parts of Central Sulawesi, Indonesia.
  • 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e155fc02688190b6f070882b846516 completed April 16, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa94e9b548190bec74e6d9790d241 completed May 9, 2026, 9:38 p.m.
NEDg Description generation batch_69ffaa07df788190bae67f3d9a800331 completed May 9, 2026, 9:41 p.m.
NED2 Entity disambiguation (via description) batch_69ffaaa92a648190a09829ef3197223c completed May 9, 2026, 9:44 p.m.
Created at: April 10, 2026, 4:51 a.m.