Triple

T22932896
Position Surface form Disambiguated ID Type / Status
Subject Kaili–Pamona languages E569488 entity
Predicate hasMember P10 FINISHED
Object Tomi language NE NERFINISHED

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: Tomi language | Statement: [Kaili–Pamona languages, hasMember, Tomi language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tomi language
Context triple: [Kaili–Pamona languages, hasMember, Tomi language]
  • A. Tomini languages chosen
    The Tomini languages are a group of closely related Austronesian languages spoken primarily along the northern coast of Central Sulawesi, Indonesia.
  • B. Tanema language
    Tanema is a nearly extinct Oceanic language once spoken on Vanikoro Island in the Temotu Province of the Solomon Islands.
  • C. Tumari language
    The Tumari language is a lesser-known Saharan language spoken by communities in parts of the central Sahara region of Africa.
  • D. Pokomo language
    The Pokomo language is a Bantu language spoken primarily by the Pokomo people along Kenya’s Tana River.
  • E. Teguima language
    The Teguima language is an extinct Uto-Aztecan language once spoken by the Opata people of northern Mexico.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2458f7d008190901dccbaebeaba24 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f181337ff881909d90cf3f5bae7516 completed April 29, 2026, 3:55 a.m.
Created at: April 17, 2026, 3:44 p.m.