Triple

T12400045
Position Surface form Disambiguated ID Type / Status
Subject Djuanda Kartawidjaja E296227 entity
Predicate birthPlace P1 FINISHED
Object Tasikmalaya E40970 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: Tasikmalaya | Statement: [Djuanda Kartawidjaja, birthPlace, Tasikmalaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tasikmalaya
Context triple: [Djuanda Kartawidjaja, birthPlace, Tasikmalaya]
  • A. Tasikmalaya chosen
    Tasikmalaya is a significant city in West Java, Indonesia, known as an important cultural and economic hub for the Sundanese people.
  • B. Cimahi
    Cimahi is an urban city in Indonesia located near Bandung in the province of West Java, known historically as a military and training center.
  • C. Sukabumi
    Sukabumi is a city in southwestern West Java, Indonesia, known for its cool climate, surrounding highlands, and proximity to popular natural attractions.
  • 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. Tasikmalaya Regency
    Tasikmalaya Regency is an administrative region in West Java, Indonesia, known for its mountainous landscapes, Islamic educational institutions, and traditional handicrafts.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9401cbfd481908ee6e765da3d12cb completed April 10, 2026, 6:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63482af8c8190b277b36371979f5e completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:55 p.m.