Triple

T22113846
Position Surface form Disambiguated ID Type / Status
Subject Parahyangan Plateau E546486 entity
Predicate hasMajorCity P316 FINISHED
Object Cimahi 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: Cimahi | Statement: [Parahyangan Plateau, hasMajorCity, Cimahi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cimahi
Context triple: [Parahyangan Plateau, hasMajorCity, Cimahi]
  • A. Cimahi chosen
    Cimahi is an urban city in Indonesia located near Bandung in the province of West Java, known historically as a military and training center.
  • B. Tasikmalaya
    Tasikmalaya is a significant city in West Java, Indonesia, known as an important cultural and economic hub for the Sundanese people.
  • C. Jatinangor
    Jatinangor is a town in West Java, Indonesia, known as a major educational hub hosting several prominent university campuses.
  • D. Bogor
    Bogor is a city on the Indonesian island of Java known for its cool climate, botanical gardens, and role as a major educational and research center.
  • E. Sukabumi
    Sukabumi is a city in southwestern West Java, Indonesia, known for its cool climate, surrounding highlands, and proximity to popular natural attractions.
  • 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_69f1294b9d5c8190897b760ca4f3b09a completed April 28, 2026, 9:40 p.m.
Created at: April 16, 2026, 8:31 p.m.