Triple

T8758101
Position Surface form Disambiguated ID Type / Status
Subject Pemon language E208122 entity
Predicate hasDialect P4251 FINISHED
Object Arekuna E547847 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: Arekuna | Statement: [Pemon language, hasDialect, Arekuna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arekuna
Context triple: [Pemon language, hasDialect, Arekuna]
  • A. Arekuna chosen
    Arekuna are an Indigenous people of the Guiana Highlands region in northern South America, culturally and linguistically related to other Cariban-speaking groups.
  • B. Erakor
    Erakor is a small island and settlement near Efate in Vanuatu, known for its lagoon setting and traditional village life.
  • C. Lastarria
    Lastarria is a historic and bohemian neighborhood in central Santiago, Chile, known for its cultural venues, restaurants, and vibrant street life.
  • D. Nakoruru
    Nakoruru is a popular Samurai Shodown character known as a nature-loving Ainu shrine maiden who fights alongside her hawk and wolf companions.
  • E. Aukena
    Aukena is a small inhabited island in the Gambier Islands of French Polynesia, known for its historical Catholic mission sites and scenic lagoon setting.
  • 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_69ca835cd6b08190bd7c63db92f53c86 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5ddc2d9c81908948aee2b956cce4 completed March 31, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf434232d08190bfee6f5ec1c0b5a6 completed April 3, 2026, 4:34 a.m.
Created at: March 30, 2026, 6:40 p.m.