Triple

T1284632
Position Surface form Disambiguated ID Type / Status
Subject Meso-Melanesian languages E27405 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Lengo E147941 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: Lengo | Statement: [Meso-Melanesian languages, hasMemberLanguage, Lengo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lengo
Context triple: [Meso-Melanesian languages, hasMemberLanguage, Lengo]
  • A. Dili
    Dili is the coastal capital and largest city of Timor-Leste, serving as its political, economic, and cultural center.
  • B. Kichwa
    Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
  • C. Blablanga chosen
    Blablanga is an Austronesian language spoken in the Solomon Islands, belonging to the Meso-Melanesian subgroup.
  • D. Kalanga
    Kalanga is a Southern Bantu language spoken primarily in southwestern Zimbabwe and northeastern Botswana by the Kalanga people.
  • E. Winaray
    Winaray is an Austronesian language spoken primarily in the Eastern Visayas region of the Philippines, particularly in Samar, northern Leyte, and nearby areas.
  • 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_69a496d4ec448190ad653b2590c46711 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0b6dda48190a2e79084adea6ec1 completed March 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69acb2ff0d4c8190893901e041f30171 completed March 7, 2026, 11:21 p.m.
Created at: March 1, 2026, 7:50 p.m.