Triple

T6902587
Position Surface form Disambiguated ID Type / Status
Subject Parameswara E159528 entity
Predicate originCity P1041 FINISHED
Object Palembang E88175 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: Palembang | Statement: [Parameswara, originCity, Palembang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palembang
Context triple: [Parameswara, originCity, Palembang]
  • A. Palembang chosen
    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.
  • 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. Makassar
    Makassar is a major port city on the southwest coast of Sulawesi known historically as a key maritime trading hub in eastern Indonesia.
  • D. 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.
  • 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_69c6883822e0819091e321526f20ae0a completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d98749208190842ac075255ca249 completed March 27, 2026, 7:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c748f6640481908b74903a47e1eb18 completed March 28, 2026, 3:20 a.m.
Created at: March 27, 2026, 2:25 p.m.