Triple

T26215720
Position Surface form Disambiguated ID Type / Status
Subject Kawi-Butak mountain complex E655619 entity
Predicate countrySubdivision P766 FINISHED
Object Regency of Malang
The Regency of Malang is an administrative region in East Java, Indonesia, known for its diverse landscapes, including mountains, agricultural areas, and growing urban centers surrounding the city of Malang.
E1716900 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: Regency of Malang | Statement: [Kawi-Butak mountain complex, countrySubdivision, Regency of Malang]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Regency of Malang
Triple: [Kawi-Butak mountain complex, countrySubdivision, Regency of Malang]
Generated description
The Regency of Malang is an administrative region in East Java, Indonesia, known for its diverse landscapes, including mountains, agricultural areas, and growing urban centers surrounding the city of Malang.

Provenance (5 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_69ee5b4a77e08190bfcb5f8ecdc55abd completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60d1ade688190b3ffdae556e903a5 completed May 2, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118fa46d1c8190ba40d3a37d9f854a completed May 23, 2026, 11:29 a.m.
NEDg Description generation batch_6a11902e8fa08190a631fab5541f89ca completed May 23, 2026, 11:31 a.m.
NED2 Entity disambiguation (via description) batch_6a119094eaf88190a68b09d1ec79b634 completed May 23, 2026, 11:33 a.m.
Created at: April 26, 2026, 8:54 p.m.