Triple

T1534394
Position Surface form Disambiguated ID Type / Status
Subject Toronto streetcar system E32517 entity
Predicate depot P14646 FINISHED
Object Leslie Barns
Leslie Barns is a modern streetcar maintenance and storage facility in Toronto that supports the city’s light rail fleet.
E190819 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: Leslie Barns | Statement: [Toronto streetcar system, depot, Leslie Barns]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leslie Barns
Context triple: [Toronto streetcar system, depot, Leslie Barns]
  • A. Leslie Harter
    Leslie Harter is a film producer known for her work in Hollywood and for being married to director Robert Zemeckis.
  • B. Leslie Fenton
    Leslie Fenton was a British-born American actor and film director active in Hollywood during the early to mid-20th century.
  • C. Nancy Gates
    Nancy Gates was an American film and television actress active from the 1940s through the 1960s, known for her roles in dramas, film noirs, and romantic comedies.
  • D. Barbara Duncan
    Barbara Duncan was the second wife of Harry Hopkins, a key advisor to U.S. President Franklin D. Roosevelt during the New Deal and World War II.
  • E. Laurie Logue
    Laurie Logue is one of the children of Australian speech therapist Lionel Logue, who is renowned for helping King George VI overcome his stammer.
  • 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: Leslie Barns
Triple: [Toronto streetcar system, depot, Leslie Barns]
Generated description
Leslie Barns is a modern streetcar maintenance and storage facility in Toronto that supports the city’s light rail fleet.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Leslie Barns
Target entity description: Leslie Barns is a modern streetcar maintenance and storage facility in Toronto that supports the city’s light rail fleet.
  • A. Leslie Harter
    Leslie Harter is a film producer known for her work in Hollywood and for being married to director Robert Zemeckis.
  • B. Leslie Fenton
    Leslie Fenton was a British-born American actor and film director active in Hollywood during the early to mid-20th century.
  • C. Nancy Gates
    Nancy Gates was an American film and television actress active from the 1940s through the 1960s, known for her roles in dramas, film noirs, and romantic comedies.
  • D. Barbara Duncan
    Barbara Duncan was the second wife of Harry Hopkins, a key advisor to U.S. President Franklin D. Roosevelt during the New Deal and World War II.
  • E. Laurie Logue
    Laurie Logue is one of the children of Australian speech therapist Lionel Logue, who is renowned for helping King George VI overcome his stammer.
  • 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61f8df00819086f34847e2170e12 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad797907ac81908ede43626798827d completed March 8, 2026, 1:28 p.m.
NEDg Description generation batch_69ad7a1223fc8190b7d62217c17f7517 completed March 8, 2026, 1:30 p.m.
NED2 Entity disambiguation (via description) batch_69ad7b0787c88190a59a815fa808ac6b completed March 8, 2026, 1:35 p.m.
Created at: March 4, 2026, 7:26 p.m.