Triple

T10681451
Position Surface form Disambiguated ID Type / Status
Subject Pesa E251764 entity
Predicate hasBrand P1500 FINISHED
Object Pesa Swing
Pesa Swing is a low-floor light rail and tram vehicle model produced by the Polish manufacturer Pesa for urban public transport systems.
 E878863 NE FINISHED

How this triple was built (4 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: Pesa Swing | Statement: [Pesa, hasBrand, Pesa Swing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pesa Swing
Context triple: [Pesa, hasBrand, Pesa Swing]
  • A. The See-Saw
    The See-Saw is a playful Rococo painting by Jean-Honoré Fragonard that depicts elegantly dressed figures enjoying a garden pastime with a light, flirtatious atmosphere.
  • B. Pengo
    Pengo is a Dravidian language spoken primarily by the Pengo people in parts of central India, especially in Odisha and neighboring regions.
  • C. Seesaw
    Seesaw is a 1973 Broadway musical with music by Cy Coleman and lyrics by Dorothy Fields, known for its New York City setting and for showcasing Tommy Tune’s Tony Award–winning performance.
  • D. The Peg
    The Peg is a colloquial nickname for Winnipeg, the capital and largest city of the Canadian province of Manitoba.
  • E. Saidi Swing
    Saidi Swing is a musical track featured on the genre-blending compilation album "A Playlist Without Borders."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Pesa Swing
Triple: [Pesa, hasBrand, Pesa Swing]
Generated description
Pesa Swing is a low-floor light rail and tram vehicle model produced by the Polish manufacturer Pesa for urban public transport systems.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pesa Swing
Target entity description: Pesa Swing is a low-floor light rail and tram vehicle model produced by the Polish manufacturer Pesa for urban public transport systems.
  • A. The See-Saw
    The See-Saw is a playful Rococo painting by Jean-Honoré Fragonard that depicts elegantly dressed figures enjoying a garden pastime with a light, flirtatious atmosphere.
  • B. Pengo
    Pengo is a Dravidian language spoken primarily by the Pengo people in parts of central India, especially in Odisha and neighboring regions.
  • C. Seesaw
    Seesaw is a 1973 Broadway musical with music by Cy Coleman and lyrics by Dorothy Fields, known for its New York City setting and for showcasing Tommy Tune’s Tony Award–winning performance.
  • D. The Peg
    The Peg is a colloquial nickname for Winnipeg, the capital and largest city of the Canadian province of Manitoba.
  • E. Saidi Swing
    Saidi Swing is a musical track featured on the genre-blending compilation album "A Playlist Without Borders."
  • F. None of above. chosen

Provenance (5 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fcc30be481909922844b539b622d completed April 9, 2026, 1:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d98885abf88190b54ed9db779d3ff0 completed April 10, 2026, 11:32 p.m.
NEDg Description generation batch_69d98aea391c81909ec64a29053c35c1 completed April 10, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_69d98c013348819094bde38a057257b4 completed April 10, 2026, 11:47 p.m.
Created at: April 8, 2026, 9:10 p.m.