Triple

T10029639
Position Surface form Disambiguated ID Type / Status
Subject Dodol Garut E204819 entity
Predicate namedAfter P63 FINISHED
Object Garut E40449 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: Garut | Statement: [Dodol Garut, namedAfter, Garut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garut
Context triple: [Dodol Garut, namedAfter, Garut]
  • A. Garut chosen
    Garut is a regency and town in West Java, Indonesia, known for its Sundanese culture, cool highland climate, and agricultural products such as vegetables and sheep.
  • B. Subang
    Subang is a town in the state of Selangor, Malaysia, that forms part of the greater Kuala Lumpur metropolitan area and serves as an important suburban and commercial hub.
  • 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. Brebes
    Brebes is a regency and major urban center in the northwestern part of Central Java, Indonesia, known for its agriculture and salted egg production.
  • E. Purwakarta Regency
    Purwakarta Regency is an administrative region in West Java, Indonesia, known for its industrial areas, transportation links, and proximity to major urban centers like Bandung and Jakarta.
  • 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_69ca834d77188190ad645e33e8ca3200 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcde69bd08190a5c79ec8487dfff6 completed April 2, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69d90d54c32c8190b175a30c7c905cd2 completed April 10, 2026, 2:46 p.m.
Created at: March 30, 2026, 8:54 p.m.