Triple

T8179178
Position Surface form Disambiguated ID Type / Status
Subject Claret operations E191015 entity
Predicate location 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: [Claret operations, location, Sabah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabah
Context triple: [Claret operations, location, 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_69ca82c4538081909404325aa5639483 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4abd9768819091298e4dd995ac96 completed March 31, 2026, 4:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69cced6fd33081909512adbe559b2c7a completed April 1, 2026, 10:03 a.m.
Created at: March 30, 2026, 5:40 p.m.