Triple

T6550575
Position Surface form Disambiguated ID Type / Status
Subject Zapin Johor E151117 entity
Predicate locatedIn P40 FINISHED
Object Johor E40971 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: Johor | Statement: [Zapin Johor, locatedIn, Johor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johor
Context triple: [Zapin Johor, locatedIn, Johor]
  • A. Johor chosen
    Johor is a state in southern Peninsular Malaysia known for its strategic location bordering Singapore, diverse economy, and rich Malay cultural heritage.
  • 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. Negeri Sembilan
    Negeri Sembilan is a state in western Peninsular Malaysia known for its Minangkabau cultural heritage and distinctive traditional architecture.
  • 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. Terengganu
    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.
  • 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_69c687f3fd60819083bfa583e5bcfa71 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6ae04affc8190826ee033849f2d42 completed March 27, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d55113408190b96baf2747f36e3c completed March 27, 2026, 7:06 p.m.
Created at: March 27, 2026, 1:51 p.m.