Triple

T1479686
Position Surface form Disambiguated ID Type / Status
Subject Nusa Tenggara E30923 entity
Predicate hasPart P35 FINISHED
Object Rinca E124633 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: Rinca | Statement: [Nusa Tenggara, hasPart, Rinca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rinca
Context triple: [Nusa Tenggara, hasPart, Rinca]
  • A. Rinca chosen
    Rinca is an Indonesian island in the Lesser Sunda chain, renowned as one of the primary habitats of the Komodo dragon within Komodo National Park.
  • B. Urup
    Urup is a volcanic island in the central Kuril Islands chain in the northwest Pacific Ocean, known for its rugged terrain and sparse human presence.
  • C. Reisa National Park
    Reisa National Park is a protected wilderness area in northern Norway known for its deep river canyon, waterfalls, and rugged Arctic landscapes.
  • D. Nusa Kode
    Nusa Kode is a small, remote island within Indonesia’s Komodo archipelago, known for its rugged terrain, rich marine life, and populations of Komodo dragons.
  • E. Ronga
    Ronga is a Bantu language spoken primarily in southern Mozambique, known for contributing vocabulary and structural features to African varieties of Portuguese.
  • 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c674cc9c819088fc9146c7a7a914 completed March 1, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad15aff1288190a3e36324d975d482 completed March 8, 2026, 6:22 a.m.
Created at: March 1, 2026, 8:11 p.m.