Triple

T12036923
Position Surface form Disambiguated ID Type / Status
Subject Kinabalu Park E286563 entity
Predicate locatedIn P40 FINISHED
Object Sabah E57487 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: Sabah | Statement: [Kinabalu Park, locatedIn, Sabah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabah
Context triple: [Kinabalu Park, locatedIn, Sabah]
  • A. Sabah chosen
    Sabah is a Malaysian state on the northern portion of Borneo, known for its rich biodiversity, indigenous cultures, and iconic Mount Kinabalu.
  • B. Sabah
    Sabah is a major Turkish daily newspaper known for its wide circulation and coverage of national news, politics, and entertainment.
  • C. Sarawak
    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.
  • D. Kayah State
    Kayah State is a small, mountainous administrative region in eastern Myanmar known for its diverse ethnic communities, including various Karen groups, and its long history of political marginalization and conflict.
  • E. Tawau
    Tawau is a coastal town and major economic hub in southeastern Sabah, Malaysia, known for its port, agriculture, and proximity to Indonesia.
  • 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_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040a8be881908f4841145a7b4e86 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d8a9af881909e28783b0d83ed82 completed May 1, 2026, 12:33 p.m.
Created at: April 8, 2026, 9:47 p.m.