Triple

T6184749
Position Surface form Disambiguated ID Type / Status
Subject Iban language E138028 entity
Predicate region P40 FINISHED
Object Sarawak E29216 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: Sarawak | Statement: [Iban language, region, Sarawak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarawak
Context triple: [Iban language, region, Sarawak]
  • A. Sarawak chosen
    Sarawak is a resource-rich Malaysian state on the island of Borneo, known for its diverse indigenous cultures, extensive rainforests, and long history under the rule of the White Rajahs before joining Malaysia.
  • B. Sabah
    Sabah is a Malaysian state on the northern portion of Borneo, known for its rich biodiversity, indigenous cultures, and iconic Mount Kinabalu.
  • C. Perak
    Perak is a Malaysian state on the west coast of the Malay Peninsula, historically known for its rich tin deposits and former status as a key sultanate within British Malaya.
  • D. East Malaysia
    East Malaysia is the portion of Malaysia located on the island of Borneo, comprising the states of Sabah and Sarawak and the federal territory of Labuan.
  • E. Pahang
    Pahang is a large Malaysian state on the eastern coast of Peninsular Malaysia, known for its extensive rainforests, highlands like Cameron Highlands, and long South China Sea coastline.
  • 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_69c008a8fd408190b7ec6e42934974a6 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c061020d148190ae2edf2b363f1e24 completed March 22, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c243d333e48190b1cb9ffd769f5473 completed March 24, 2026, 7:57 a.m.
Created at: March 22, 2026, 4:19 p.m.