Triple

T22159673
Position Surface form Disambiguated ID Type / Status
Subject Regent of Tabanan E547633 entity
Predicate residence P75 FINISHED
Object Tabanan NE NERFINISHED

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: Tabanan | Statement: [Regent of Tabanan, residence, Tabanan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tabanan
Context triple: [Regent of Tabanan, residence, Tabanan]
  • A. Tuban
    Tuban is a major city in Yemen’s Lahij Governorate, serving as an important local center for administration and commerce.
  • B. Tuban
    Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
  • C. Tabanan Regency chosen
    Tabanan Regency is an agricultural and coastal region in western Bali, Indonesia, known for its lush rice terraces and the iconic Tanah Lot sea temple.
  • D. Citeureup
    Citeureup is a district in West Java, Indonesia, known as one of the industrial and residential areas within the Bogor metropolitan region.
  • E. Ambarawa
    Ambarawa is a town in Central Java, Indonesia, known as a historical area near the ancient Gedong Songo Hindu temple complex and former colonial-era military sites.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e3c4c5c81908d336165816b12e0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12a2c17a4819082fb9e4aaa275462 completed April 28, 2026, 9:44 p.m.
Created at: April 16, 2026, 8:33 p.m.