Triple

T9032359
Position Surface form Disambiguated ID Type / Status
Subject Zunheboto E216401 entity
Predicate hasLocalLanguage P4185 FINISHED
Object Sumi language E644030 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: Sumi language | Statement: [Zunheboto, hasLocalLanguage, Sumi language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sumi language
Context triple: [Zunheboto, hasLocalLanguage, Sumi language]
  • A. Sumi language chosen
    Sumi language is a Sino-Tibetan language spoken primarily by the Sumi Naga people in the Indian state of Nagaland.
  • B. Suma language
    The Suma language is a lesser-known Gbaya language spoken by the Suma people in parts of Central Africa.
  • C. Khumi language
    The Khumi language is a lesser-known Tibeto-Burman language spoken primarily by the Khumi people in parts of Myanmar and neighboring regions.
  • D. Kisukuma language
    Kisukuma is a major Bantu language spoken primarily by the Sukuma people in northwestern Tanzania.
  • E. Rumsen language
    Rumsen language is an extinct Ohlone (Costanoan) Native American language formerly spoken in the Monterey Bay area of California.
  • 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_69ca83d10b608190b2b2f8e0a7faaf14 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc6aa0c89c81909792190f08fef8df completed April 1, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdbc9c6e08190aa71d84316afc6d5 completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:08 p.m.