Triple

T10062890
Position Surface form Disambiguated ID Type / Status
Subject South Kalimantan E213030 entity
Predicate largestCity P235 FINISHED
Object Banjarmasin E74310 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: Banjarmasin | Statement: [South Kalimantan, largestCity, Banjarmasin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Banjarmasin
Context triple: [South Kalimantan, largestCity, Banjarmasin]
  • A. Banjarmasin chosen
    Banjarmasin is a major riverine city in South Kalimantan, Indonesia, known for its historic floating markets and strategic location on the island of Borneo.
  • B. 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.
  • C. Palembang
    Palembang is a major Indonesian city on the island of Sumatra, historically known as the center of the Srivijaya maritime empire and now an important economic and cultural hub.
  • D. Palangka Raya
    Palangka Raya is the largest city and administrative center of Indonesia’s Central Kalimantan province on the island of Borneo.
  • E. Balikpapan
    Balikpapan is a coastal city in East Kalimantan, Indonesia, known as a major oil and gas hub and one of the most developed urban centers on the island of Borneo.
  • 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_69ca83977128819084084eb7d1d8c52a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdcfd4e4ac8190a37061b4082caa48 completed April 2, 2026, 2:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b630ca008190a337660ad8c9d57e completed April 5, 2026, 7:21 p.m.
Created at: March 30, 2026, 8:58 p.m.