Triple

T6216926
Position Surface form Disambiguated ID Type / Status
Subject Central Kalimantan E139010 entity
Predicate largestCity P235 FINISHED
Object Palangka Raya E577077 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: Palangka Raya | Statement: [Central Kalimantan, largestCity, Palangka Raya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palangka Raya
Context triple: [Central Kalimantan, largestCity, Palangka Raya]
  • A. Palangka Raya chosen
    Palangka Raya is the largest city and administrative center of Indonesia’s Central Kalimantan province on the island of Borneo.
  • B. Banjarmasin
    Banjarmasin is a major riverine city in South Kalimantan, Indonesia, known for its historic floating markets and strategic location on the island of Borneo.
  • C. Samarinda
    Samarinda is the capital and largest city of Indonesia’s East Kalimantan province on the island of Borneo, known as a key regional center for trade, industry, and river transport along the Mahakam River.
  • D. Padang Besar
    Padang Besar is a border town in northern Malaysia known as a key land gateway and trading hub between Malaysia and Thailand.
  • E. Bengkulu
    Bengkulu is a province on the southwest coast of the Indonesian island of Sumatra, known for its Indian Ocean shoreline and colonial history.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062a1eb3881908c7f735cf9c429ce completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c243e998e0819090a2162e2a0ab7b9 completed March 24, 2026, 7:57 a.m.
Created at: March 22, 2026, 4:21 p.m.