Triple

T21781579
Position Surface form Disambiguated ID Type / Status
Subject North Lombok Regency E537725 entity
Predicate seatOfGovernment P761 FINISHED
Object Tanjung 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: Tanjung | Statement: [North Lombok Regency, seatOfGovernment, Tanjung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanjung
Context triple: [North Lombok Regency, seatOfGovernment, Tanjung]
  • A. Tanjung chosen
    Tanjung is a coastal town on the Indonesian island of Lombok that serves as an administrative and commercial hub for the surrounding region.
  • B. Tanjung Cho
    Tanjung Cho is one of the high-altitude glacial lakes in the Gokyo Lakes system of Nepal’s Everest region, known for its striking turquoise waters and dramatic Himalayan surroundings.
  • C. Tanjung Raya
    Tanjung Raya is a district in West Sumatra, Indonesia, known for encompassing the scenic area around Lake Maninjau and its surrounding highland landscapes.
  • D. Tanjung Aan
    Tanjung Aan is a scenic white-sand beach and popular coastal tourist destination on the southern coast of Lombok, Indonesia.
  • E. Tanjung Bira
    Tanjung Bira is a popular beach destination in South Sulawesi, Indonesia, known for its white sand, clear turquoise waters, and diving and snorkeling spots.
  • 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_69e0c47198f881908cb0d237266c10e9 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0462db0208190ad31c132d3f875bc completed April 28, 2026, 5:31 a.m.
Created at: April 16, 2026, 6:52 p.m.