Triple

T7840775
Position Surface form Disambiguated ID Type / Status
Subject Kediri E181796 entity
Predicate railConnection P848 FINISHED
Object Malang E28882 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: Malang | Statement: [Kediri, railConnection, Malang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malang
Context triple: [Kediri, railConnection, Malang]
  • A. Malang chosen
    Malang is a major city in East Java, Indonesia, known for its cool climate, colonial-era architecture, and proximity to popular mountain and volcanic tourist destinations.
  • B. Surabaya
    Surabaya is Indonesia’s second-largest city and a key commercial and industrial hub on the island of Java, historically serving as one of the region’s most important seaports.
  • C. Malang Regency
    Malang Regency is an administrative region in East Java, Indonesia, known for its mountainous landscapes, cool climate, and proximity to popular tourist destinations such as Batu and Mount Bromo.
  • D. Kediri
    Kediri is a historic city in Indonesia known for its role as a former Javanese kingdom center and as an important economic hub in modern East Java.
  • E. Jember
    Jember is a regency and major urban center in eastern Java, Indonesia, known for its agricultural economy and cultural festivals such as the Jember Fashion Carnaval.
  • 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_69ca8285d6488190a95d4c02d7354b53 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb14c589748190b34d0911d373e194 completed March 31, 2026, 12:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc639b68a4819080acfca35e498cfa completed April 1, 2026, 12:15 a.m.
Created at: March 30, 2026, 4:47 p.m.