Triple

T6564840
Position Surface form Disambiguated ID Type / Status
Subject Mwerlap E153876 entity
Predicate hasAlternativeName P39 FINISHED
Object Merelava E603826 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: Merelava | Statement: [Mwerlap, hasAlternativeName, Merelava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Merelava
Context triple: [Mwerlap, hasAlternativeName, Merelava]
  • A. Merelava chosen
    Merelava is a small volcanic island in northern Vanuatu, known for its steep terrain, active cultural traditions, and use of the Mwerlap language by its inhabitants.
  • B. Vunisea
    Vunisea is a small coastal village that serves as the administrative and commercial center of Kadavu Island in Fiji.
  • C. Muribenua
    Muribenua is a village on the low-lying coral atoll of Nikunau in the Republic of Kiribati, a Pacific island nation.
  • D. Makarora
    Makarora is a small rural settlement in New Zealand’s South Island, known as a gateway to outdoor activities and hiking in the Southern Alps region.
  • E. Tamba
    Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
  • 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_69c6880cb35881909b763eb0125236b9 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae3b9ec8819080f3052556d95810 completed March 27, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e42523848190b02682e6a640ac05 completed March 27, 2026, 8:10 p.m.
Created at: March 27, 2026, 1:52 p.m.