Triple

T9577719
Position Surface form Disambiguated ID Type / Status
Subject Sawunese language E231085 entity
Predicate closelyRelatedTo P37 FINISHED
Object Dhao language E231083 NE FINISHED

How this triple was built (2 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: Dhao language | Statement: [Sawunese language, closelyRelatedTo, Dhao language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dhao language
Context triple: [Sawunese language, closelyRelatedTo, Dhao language]
  • A. Dhanka language
    Dhanka is an Indo-Aryan tribal language variety considered a dialect within the Bhili language group of western India.
  • B. Thadou language
    Thadou language is a Kuki-Chin language spoken primarily by the Thadou people in northeastern India and neighboring regions.
  • C. Rengma language
    Rengma language is a Tibeto-Burman language spoken primarily by the Rengma Naga people in the northeastern region of India.
  • D. Dawan language chosen
    The Dawan language is an Austronesian language spoken primarily in West Timor, Indonesia, by the Atoni people.
  • E. Dawro language
    The Dawro language is an Omotic language of southwestern Ethiopia spoken by the Dawro people and closely related to Wolaytta.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca848091c48190bc313d6620d09555 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99ad7d108190a0b8c975351ea727 completed April 1, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69d16155b3288190ac135c3a1e58cc7e completed April 4, 2026, 7:07 p.m.
Created at: March 30, 2026, 8:05 p.m.