Triple

T5635821
Position Surface form Disambiguated ID Type / Status
Subject Fataleka E147945 entity
Predicate spokenIn P2266 FINISHED
Object Malaita Province E112973 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: Malaita Province | Statement: [Fataleka, spokenIn, Malaita Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malaita Province
Context triple: [Fataleka, spokenIn, Malaita Province]
  • A. Malaita Province chosen
    Malaita Province is one of the main provinces of the Solomon Islands, centered on the large and densely populated island of Malaita in the country’s eastern region.
  • B. Makira-Ulawa Province
    Makira-Ulawa Province is an island province in the Solomon Islands, known for its rugged landscapes, rich biodiversity, and predominantly subsistence-based rural communities.
  • C. Simbu Province
    Simbu Province is a mountainous inland province in central Papua New Guinea known for its rugged terrain, highland cultures, and traditional agricultural communities.
  • D. Tata Province
    Tata Province is an administrative region in southern Morocco known for its desert landscapes, oases, and Berber cultural heritage.
  • E. Enga Province
    Enga Province is a rugged, landlocked province in Papua New Guinea known for its high-altitude landscapes, rich traditional cultures, and significant mineral resources.
  • 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_69c00907bc8881909ed760d3ed73ef35 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0226286208190b6ccf036cc09fe82 completed March 22, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c124e449d481909a6aa8e1c6494322 completed March 23, 2026, 11:32 a.m.
Created at: March 22, 2026, 3:41 p.m.