Triple

T22121031
Position Surface form Disambiguated ID Type / Status
Subject Kampar railway station E546665 entity
Predicate serves P98 FINISHED
Object Kampar NE NERFINISHED

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: Kampar | Statement: [Kampar railway station, serves, Kampar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kampar
Context triple: [Kampar railway station, serves, Kampar]
  • A. Kampar chosen
    Kampar is a town and district in Perak, Malaysia, historically notable as the site of a major World War II battle between British Commonwealth and Japanese forces.
  • B. Lebong
    Lebong is a historical region in southwestern Sumatra, Indonesia, traditionally associated with the Rejang people and their distinctive script.
  • C. Rantau
    Rantau is a state constituency in Malaysia’s Negeri Sembilan state, represented in the Negeri Sembilan State Legislative Assembly.
  • D. Rantau
    Rantau is a town in South Kalimantan, Indonesia, known as an administrative and economic center in the region.
  • E. Kampar Regency
    Kampar Regency is an administrative region in Riau Province, Indonesia, known for its riverside landscapes, agricultural activities, and proximity to the Kampar River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e38b3848190ac3a4fa97d56e65a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f12951fcd48190841319cd879c15cb completed April 28, 2026, 9:40 p.m.
Created at: April 16, 2026, 8:31 p.m.