Triple

T10029824
Position Surface form Disambiguated ID Type / Status
Subject Taman Negara E204823 entity
Predicate locatedIn P40 FINISHED
Object Terengganu E43798 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: Terengganu | Statement: [Taman Negara, locatedIn, Terengganu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terengganu
Context triple: [Taman Negara, locatedIn, Terengganu]
  • A. Terengganu chosen
    Terengganu is a state on the eastern coast of Peninsular Malaysia, known for its traditional Malay culture, Islamic heritage, and scenic islands and beaches along the South China Sea.
  • B. Kelantan
    Kelantan is a northeastern Malaysian state on the Malay Peninsula, known for its strong Malay cultural traditions, Islamic influence, and capital city Kota Bharu.
  • C. Perlis
    Perlis is Malaysia’s smallest state, located in the northern part of the Malay Peninsula bordering Thailand and known for its agricultural landscape and quiet rural character.
  • D. 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.
  • E. Kuala Perlis
    Kuala Perlis is a small coastal town in Malaysia known as a key ferry gateway to the resort island of Langkawi.
  • 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_69ca834d77188190ad645e33e8ca3200 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcde69bd08190a5c79ec8487dfff6 completed April 2, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6554d0b0081909cc031ff06b796c0 completed May 2, 2026, 7:49 p.m.
Created at: March 30, 2026, 8:54 p.m.