Triple

T2107585
Position Surface form Disambiguated ID Type / Status
Subject Odia script E42429 entity
Predicate usedFor P98 FINISHED
Object Ho language E199648 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: Ho language | Statement: [Odia script, usedFor, Ho language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ho language
Context triple: [Odia script, usedFor, Ho language]
  • A. Ho language chosen
    Ho language is an Austroasiatic language of the Munda family spoken primarily by the Ho people in eastern India, particularly in Jharkhand and Odisha.
  • B. Ha language
    Ha language is a Bantu language spoken primarily by the Ha people in western Tanzania, particularly around the shores of Lake Tanganyika.
  • C. Hoava language
    The Hoava language is an Oceanic language spoken by communities in the western Solomon Islands, particularly on New Georgia Island.
  • D. Mon language
    Mon language is an Austroasiatic language historically spoken in parts of Myanmar and Thailand, notable for its ancient literary tradition and influence on regional scripts and cultures.
  • E. Hoanya language
    The Hoanya language is an extinct Austronesian language once spoken by the Hoanya people of western Taiwan and classified among the indigenous Formosan languages.
  • 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_69a8871040f08190aac2e2d0ab6b47ad completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbadf12b88190acc513d8512777b2 completed March 7, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae306e040081909334f2a70036c26e completed March 9, 2026, 2:29 a.m.
Created at: March 4, 2026, 7:43 p.m.