Triple

T3990532
Position Surface form Disambiguated ID Type / Status
Subject Rencong script E86977 entity
Predicate geographicDistribution P2178 FINISHED
Object Lampung E99876 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: Lampung | Statement: [Rencong script, geographicDistribution, Lampung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lampung
Context triple: [Rencong script, geographicDistribution, Lampung]
  • A. Lampung chosen
    Lampung is a province at the southern tip of the Indonesian island of Sumatra, known for its coastal landscapes, agriculture, and proximity to the Sunda Strait.
  • B. Bengkulu
    Bengkulu is a province on the southwest coast of the Indonesian island of Sumatra, known for its Indian Ocean shoreline and colonial history.
  • C. Banten
    Banten is a province on the western tip of Indonesia’s Java Island, known for its coastal trade history, cultural heritage, and proximity to the capital city Jakarta.
  • D. Riau
    Riau is a resource-rich Indonesian province on the central eastern coast of Sumatra, known for its oil, gas, and palm oil industries and its strategic location along the Strait of Malacca.
  • E. Jambi
    Jambi is a province on the eastern coast of central Sumatra in Indonesia, known for its oil production, plantations, and the Batanghari River.
  • 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_69aed93fd9d4819085d3b2137d2346cb completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa01bf3c8190a6fb3bba65186ae6 completed March 9, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5561f0a2881909d758a8fba58309d completed March 14, 2026, 12:35 p.m.
Created at: March 9, 2026, 3:33 p.m.