Triple

T18738555
Position Surface form Disambiguated ID Type / Status
Subject Bandung–Garut railway E458229 entity
Predicate hasEndpointStation P34947 FINISHED
Object Bandung Station 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: Bandung Station | Statement: [Bandung–Garut railway, hasEndpointStation, Bandung Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bandung Station
Context triple: [Bandung–Garut railway, hasEndpointStation, Bandung Station]
  • A. Bandung railway station chosen
    Bandung railway station is the main rail hub in Bandung, Indonesia, serving as a key junction for intercity and regional train services across West Java and beyond.
  • B. Bogor Station
    Bogor Station is a major railway station and commuter rail terminus serving the city of Bogor and the greater Jakarta metropolitan area in Indonesia.
  • C. Bojong Gede Station
    Bojong Gede Station is a commuter rail station serving the Bojong Gede area in the Greater Jakarta region of Indonesia.
  • D. Bekasi Station
    Bekasi Station is a major railway station serving commuter and intercity trains in the city of Bekasi, Indonesia.
  • E. Sentul station
    Sentul station is a key commuter rail station in Kuala Lumpur, Malaysia, serving as an important node on the KTM Komuter network.
  • 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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5768ca990819098102f8522ce401f completed April 20, 2026, 12:42 a.m.
Created at: April 10, 2026, 11:51 a.m.