Triple

T1894044
Position Surface form Disambiguated ID Type / Status
Subject Borneo campaign (1945) E41936 entity
Predicate location P40 FINISHED
Object Borneo E15167 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: Borneo | Statement: [Borneo campaign (1945), location, Borneo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borneo
Context triple: [Borneo campaign (1945), location, Borneo]
  • A. Borneo chosen
    Borneo is the world’s third-largest island in Southeast Asia, known for its vast rainforests, rich biodiversity, and division among Indonesia, Malaysia, and Brunei.
  • B. Borneo Island
    Borneo Island is a modern residential island in Amsterdam’s Eastern Docklands, known for its contemporary architecture and waterfront urban design.
  • C. Kalimantan
    Kalimantan is the Indonesian portion of the island of Borneo, known for its vast rainforests, rich biodiversity, and significant natural resources.
  • D. Sumatra
    Sumatra is a large Indonesian island in western Indonesia known for its rich biodiversity, active volcanoes, and significant role in regional trade and history.
  • E. Celebes
    Celebes, now known as Sulawesi, is a large, uniquely shaped island in Indonesia renowned for its diverse cultures, mountainous landscapes, and rich marine biodiversity.
  • 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_69a8864b6de0819098d089f6a1b910a7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1497df08190ad90dd89f76208ca completed March 7, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae516ffd088190ae2c730e1caff8f6 completed March 9, 2026, 4:49 a.m.
Created at: March 4, 2026, 7:34 p.m.