Triple

T22933769
Position Surface form Disambiguated ID Type / Status
Subject Loinang E569516 entity
Predicate hasName P744 FINISHED
Object Loinang 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: Loinang language | Statement: [Loinang, hasName, Loinang language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loinang language
Context triple: [Loinang, hasName, Loinang language]
  • A. Loinang dialect chosen
    The Loinang dialect is a regional variety of the Saluan language spoken by communities in parts of Central Sulawesi, Indonesia.
  • B. Lango language
    Lango is a Western Nilotic language spoken primarily by the Lango people of northern Uganda, closely related to other Luo languages.
  • C. Lovono language
    The Lovono language is an Oceanic language spoken in the Temotu Province of the Solomon Islands, belonging to the Temotu subgroup of Austronesian languages.
  • D. Loniu language
    The Loniu language is an Oceanic language spoken on Loniu Island in Manus Province, Papua New Guinea.
  • E. Lavongai language
    The Lavongai language is an Austronesian language spoken by the indigenous community on New Hanover Island in Papua New Guinea.
  • 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_69f18134484c8190b7311606c17d058d completed April 29, 2026, 3:55 a.m.
Created at: April 17, 2026, 3:44 p.m.