Triple

T6550473
Position Surface form Disambiguated ID Type / Status
Subject Dondang sayang E151114 entity
Predicate region P40 FINISHED
Object Melaka E55929 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: Melaka | Statement: [Dondang sayang, region, Melaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melaka
Context triple: [Dondang sayang, region, Melaka]
  • A. Malacca chosen
    Malacca is a historic Malaysian state on the southwest coast of the Malay Peninsula, renowned for its rich multicultural heritage and its former role as a major trading port.
  • B. Penang
    Penang is a Malaysian state and island renowned for its multicultural heritage, historic George Town, and vibrant street food scene.
  • C. Johor Bahru
    Johor Bahru is a large, rapidly developing city in southern Peninsular Malaysia, located just across the causeway from Singapore and serving as the capital of Johor state.
  • D. Johor Lama
    Johor Lama was a historic fortified riverine settlement that served as an important political and trading center of the Johor Sultanate in the Malay Peninsula.
  • E. Seremban
    Seremban is the capital city of the Malaysian state of Negeri Sembilan, known as an administrative, commercial, and cultural center in the western part of Peninsular Malaysia.
  • 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.