Triple

T7408143
Position Surface form Disambiguated ID Type / Status
Subject Sawai language E170931 entity
Predicate neighboringLanguage P16383 FINISHED
Object Gane language E170929 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: Gane language | Statement: [Sawai language, neighboringLanguage, Gane language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gane language
Context triple: [Sawai language, neighboringLanguage, Gane language]
  • A. Gane language chosen
    The Gane language is an Austronesian language spoken by the Gane people in the southern part of Halmahera in eastern Indonesia.
  • B. Ghanongga language
    The Ghanongga language is an Oceanic language spoken by indigenous communities on New Georgia Island in the Solomon Islands.
  • C. Nganasan language
    The Nganasan language is a critically endangered Samoyedic language spoken by the Nganasan people of the Taymyr Peninsula in northern Siberia.
  • D. Guna language
    Guna language is an indigenous Chibchan language spoken by the Guna people of Panama and Colombia.
  • E. Gura language
    The Gura language is an Ethiopian Semitic language spoken by the Gurage people in central Ethiopia.
  • 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_69c68a6010108190925e5284de022660 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f29acf588190a7c4056bdc4f3ffc completed March 27, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81edbbe6481908904d1a1f7cfb20a completed March 28, 2026, 6:32 p.m.
Created at: March 27, 2026, 3:10 p.m.