Triple

T24471098
Position Surface form Disambiguated ID Type / Status
Subject Masjid Jami Malang E617100 entity
Predicate administeredBy P86 FINISHED
Object local Islamic council of Malang
The local Islamic council of Malang is a regional religious authority responsible for overseeing Islamic affairs, guidance, and mosque administration in the Malang area of Indonesia.
E1636214 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: local Islamic council of Malang | Statement: [Masjid Jami Malang, administeredBy, local Islamic council 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: local Islamic council of Malang
Triple: [Masjid Jami Malang, administeredBy, local Islamic council of Malang]
Generated description
The local Islamic council of Malang is a regional religious authority responsible for overseeing Islamic affairs, guidance, and mosque administration in the Malang area of Indonesia.

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_69e2d7f197588190889a03e620558059 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f299432b2881909502f9cbc7e4dbb0 completed April 29, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe3922e708190abd9672b0f47bfef completed May 22, 2026, 5:03 a.m.
NEDg Description generation batch_6a0fe6c7cf0c8190a519141e2d729f8a completed May 22, 2026, 5:16 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe76385488190991e3bd99cd9d9e9 completed May 22, 2026, 5:19 a.m.
Created at: April 18, 2026, 2:20 a.m.