Triple

T18254167
Position Surface form Disambiguated ID Type / Status
Subject Continental AG E437177 entity
Predicate hasBrand P1500 FINISHED
Object Gislaved NE NERFINISHED

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: Gislaved | Statement: [Continental AG, hasBrand, Gislaved]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gislaved
Context triple: [Continental AG, hasBrand, Gislaved]
  • A. Gislaved chosen
    Gislaved is a tire brand known for producing reliable winter and all-season tires, particularly popular in Northern and Central Europe.
  • B. Svalöv
    Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
  • C. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • D. Götene
    Götene is a small locality and municipality in western Sweden known for its rural landscape and proximity to the historic Kinnekulle plateau by Lake Vänern.
  • E. Tingsryd
    Tingsryd is a small locality and municipality in southern Sweden known for its rural landscapes, lakes, and traditional Swedish countryside character.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4fd82f81c81909ad4455954bd8caa completed April 19, 2026, 4:06 p.m.
Created at: April 10, 2026, 10:33 a.m.