Triple

T1877762
Position Surface form Disambiguated ID Type / Status
Subject Pasundan E39182 entity
Predicate associatedCity P3207 FINISHED
Object Cirebon E41237 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: Cirebon | Statement: [Pasundan, associatedCity, Cirebon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cirebon
Context triple: [Pasundan, associatedCity, Cirebon]
  • A. Cirebon chosen
    Cirebon is a coastal city in West Java, Indonesia, known as a cultural crossroads blending Sundanese and Javanese influences and serving as a significant regional trading and urban center.
  • B. 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.
  • C. Semarang
    Semarang is a major coastal city on the north coast of Java in Indonesia, known historically as an important colonial trading hub and now as a significant commercial and industrial center.
  • D. Surakarta
    Surakarta is a historic Javanese city in Central Java, Indonesia, renowned as a traditional cultural center and royal court city closely associated with classical arts such as gamelan music and dance.
  • E. Pekalongan
    Pekalongan is an Indonesian coastal city on the island of Java renowned as a major center of batik production and textile arts.
  • 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_69a8862f7074819096afe7fe65e179e9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0f79fbc819085c54f3189a552d9 completed March 7, 2026, 5 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3ca2bd48190b055dd2e657c4dd9 completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:34 p.m.