Triple

T23238341
Position Surface form Disambiguated ID Type / Status
Subject Rudy Kousbroek E581365 entity
Predicate birthPlace P1 FINISHED
Object Pematangsiantar E400884 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: Pematangsiantar | Statement: [Rudy Kousbroek, birthPlace, Pematangsiantar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pematangsiantar
Context triple: [Rudy Kousbroek, birthPlace, Pematangsiantar]
  • A. Pematangsiantar chosen
    Pematangsiantar is a major city in North Sumatra, Indonesia, known as an important economic and transportation hub in the region.
  • B. Padang Sidempuan
    Padang Sidempuan is a city in western Indonesia known as a regional center in the southern part of North Sumatra province.
  • C. Tanjungbalai
    Tanjungbalai is a coastal city and port in northeastern Sumatra, Indonesia, known for its fishing industry and location along the Asahan River.
  • D. Solok
    Solok is a city in the Indonesian province of West Sumatra known for its rice production and scenic highland landscapes.
  • E. Lubuk Pakam
    Lubuk Pakam is an administrative town in North Sumatra, Indonesia, known as a local governmental and commercial center in the region.
  • 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_69e2460556f88190be1744a84a84173f completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f192ebaef4819083a7805537ad993f completed April 29, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c3f5ea49c8190bca74c1c21e1a85b completed May 19, 2026, 10:45 a.m.
Created at: April 17, 2026, 4:10 p.m.