Triple

T2711570
Position Surface form Disambiguated ID Type / Status
Subject Johor Bahru E59872 entity
Predicate near P350 FINISHED
Object Pasir Gudang E216258 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: Pasir Gudang | Statement: [Johor Bahru, near, Pasir Gudang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pasir Gudang
Context triple: [Johor Bahru, near, Pasir Gudang]
  • A. Pasir Gudang chosen
    Pasir Gudang is an industrial port city in the state of Johor, Malaysia, known for its heavy industries and maritime activities along the Straits of Johor.
  • B. Pasir Mas
    Pasir Mas is a town in the Malaysian state of Kelantan, known as a local commercial and transport hub near the border with Thailand.
  • C. Pelabuhan Ratu
    Pelabuhan Ratu is a coastal town and bay in West Java, Indonesia, known for its scenic beaches, strong surf, and local fishing culture.
  • D. Padang Besar
    Padang Besar is a border town in northern Malaysia known as a key land gateway and trading hub between Malaysia and Thailand.
  • E. Padang Panjang
    Padang Panjang is a small highland city in West Sumatra, Indonesia, known for its Minangkabau cultural heritage and cool mountainous climate.
  • 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_69ab4ac92a088190bc74bca14038e3de completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda78c4f08190bb1217f08198c4cc completed March 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf83e37c8190b7a7815f8acf3a4b completed March 10, 2026, 5:43 a.m.
Created at: March 6, 2026, 9:55 p.m.