Triple

T13799319
Position Surface form Disambiguated ID Type / Status
Subject Lake Vänern E331596 entity
Predicate hasCityOnShore P969 FINISHED
Object Vänerborg E331595 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: Vänerborg | Statement: [Lake Vänern, hasCityOnShore, Vänerborg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vänerborg
Context triple: [Lake Vänern, hasCityOnShore, Vänerborg]
  • A. Vänersborg chosen
    Vänersborg is a Swedish town located at the southern tip of Lake Vänern, known historically as an administrative and trading center.
  • B. Västberga
    Västberga is an industrial and residential district in southern Stockholm, Sweden, known for its warehouses, logistics centers, and proximity to major transport routes.
  • C. Svalöv
    Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
  • D. Östervåla
    Östervåla is a locality in central Sweden that serves as one of the settlements within Heby Municipality in Uppsala County.
  • E. Värmskog
    Värmskog is a small locality in Värmland County, Sweden, known as the birthplace of telephone industry pioneer Lars Magnus Ericsson.
  • 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de025ce9148190b23370f6a522ff7a completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b0893a20819081d4001b8dbc9c36 completed May 3, 2026, 8:31 p.m.
Created at: April 9, 2026, 10:11 p.m.