Triple

T4703795
Position Surface form Disambiguated ID Type / Status
Subject Region XII E104339 entity
Predicate hasMunicipality P847 FINISHED
Object Lebak E285581 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: Lebak | Statement: [Region XII, hasMunicipality, Lebak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lebak
Context triple: [Region XII, hasMunicipality, Lebak]
  • A. Lebak chosen
    Lebak is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its agricultural economy and fishing communities.
  • B. Lebak Regency
    Lebak Regency is an administrative region in Banten Province on the island of Java, Indonesia, known for its rural landscapes and as the homeland of the indigenous Baduy people.
  • C. Cilegon
    Cilegon is an industrial port city in western Java, Indonesia, known for its steel industry and strategic location near the Sunda Strait.
  • D. Sukabumi
    Sukabumi is a city in southwestern West Java, Indonesia, known for its cool climate, surrounding highlands, and proximity to popular natural attractions.
  • E. Tangerang
    Tangerang is a major urban and industrial city in Indonesia located just west of Jakarta on the island of Java.
  • 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_69bd43e9b88481908582103dcadff3d9 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd63d082088190b7fc61a487d7ef2f completed March 20, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03d074348190a19092fa02a0bb39 completed March 21, 2026, 2:34 a.m.
Created at: March 20, 2026, 1:17 p.m.