Triple

T14237873
Position Surface form Disambiguated ID Type / Status
Subject Borås E352932 entity
Predicate hasRiver P165 FINISHED
Object Viskan E552087 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: Viskan | Statement: [Borås, hasRiver, Viskan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viskan
Context triple: [Borås, hasRiver, Viskan]
  • A. Viskan chosen
    Viskan is a river in southwestern Sweden that flows through the province of Halland into the Kattegat.
  • B. Viskuli
    Viskuli is a government hunting lodge in the Białowieża Forest of Belarus, historically significant as the site where the leaders of Russia, Ukraine, and Belarus signed the Belavezha Accords dissolving the Soviet Union.
  • C. Musina
    Musina is a northern South African town in Limpopo Province, known as a key border and transport hub near Zimbabwe and for its history of copper and iron ore mining.
  • D. Oliena
    Oliena is a historic town in central Sardinia, Italy, known for its traditional Barbagia culture, mountainous landscapes, and renowned Nepente di Oliena wine.
  • E. Viskase
    Viskase is a manufacturing company best known for producing cellulose and plastic casings used in the global meat and poultry processing industry.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de62422e28819089e7115052a28c96 completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd281f80548190ad489c418f27e82c completed May 8, 2026, 12:02 a.m.
Created at: April 10, 2026, 1:08 a.m.