Triple

T13588459
Position Surface form Disambiguated ID Type / Status
Subject Kereta Api Indonesia E324630 entity
Predicate hasSubsidiary P254 FINISHED
Object Reska Multi Usaha
Reska Multi Usaha is an Indonesian company that provides onboard catering, cleaning, and related support services for the national railway operator.
E1049168 NE FINISHED

How this triple was built (4 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: Reska Multi Usaha | Statement: [Kereta Api Indonesia, hasSubsidiary, Reska Multi Usaha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reska Multi Usaha
Context triple: [Kereta Api Indonesia, hasSubsidiary, Reska Multi Usaha]
  • A. Resuk
    Resuk is an indigenous local language spoken by the community on Atauro Island in Timor-Leste.
  • B. Enterprise Rupes
    Enterprise Rupes is a prominent lobate scarp on the planet Mercury, formed by the planet’s crust contracting and thrusting over itself as Mercury cooled.
  • C. New Bazaar
    New Bazaar is the English translation of "Novi Pazar," a historic town in southwestern Serbia known for its Ottoman-era architecture and multicultural heritage.
  • D. The Business
    The Business is a film featuring actor Geoff Bell in a prominent role.
  • E. Takas
    Takas is a dialect of the Mwaghavul language spoken by a subgroup of the Mwaghavul people in Nigeria’s Plateau State.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Reska Multi Usaha
Triple: [Kereta Api Indonesia, hasSubsidiary, Reska Multi Usaha]
Generated description
Reska Multi Usaha is an Indonesian company that provides onboard catering, cleaning, and related support services for the national railway operator.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Reska Multi Usaha
Target entity description: Reska Multi Usaha is an Indonesian company that provides onboard catering, cleaning, and related support services for the national railway operator.
  • A. Resuk
    Resuk is an indigenous local language spoken by the community on Atauro Island in Timor-Leste.
  • B. Enterprise Rupes
    Enterprise Rupes is a prominent lobate scarp on the planet Mercury, formed by the planet’s crust contracting and thrusting over itself as Mercury cooled.
  • C. New Bazaar
    New Bazaar is the English translation of "Novi Pazar," a historic town in southwestern Serbia known for its Ottoman-era architecture and multicultural heritage.
  • D. The Business
    The Business is a film featuring actor Geoff Bell in a prominent role.
  • E. Takas
    Takas is a dialect of the Mwaghavul language spoken by a subgroup of the Mwaghavul people in Nigeria’s Plateau State.
  • F. None of above. chosen

Provenance (5 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb054c6008190839384ce26e8f71a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bc347b881908267455f3bdd50e8 completed May 3, 2026, 3:37 p.m.
NEDg Description generation batch_69f77642e4b881909915c686a0d6c6fa completed May 3, 2026, 4:22 p.m.
NED2 Entity disambiguation (via description) batch_69f7792110e48190a29b6e89c6ebcc03 completed May 3, 2026, 4:34 p.m.
Created at: April 9, 2026, 9:49 p.m.