Triple

T789209
Position Surface form Disambiguated ID Type / Status
Subject Line 4 Sheppard E16872 entity
Predicate connectsStation P845 FINISHED
Object Leslie
Leslie is a Toronto subway station on Line 4 Sheppard in the city's transit system.
E105272 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 | Statement: [Line 4 Sheppard, connectsStation, Leslie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leslie
Context triple: [Line 4 Sheppard, connectsStation, Leslie]
  • A. Leslie
    Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
  • B. Leslie
    Leslie is the given name of Leslie R. Groves Jr., the U.S. Army Corps of Engineers officer who directed the Manhattan Project during World War II.
  • C. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • D. Lester
    Lester is a surname of Irish origin borne by various notable individuals, including the diplomat Seán Lester.
  • E. Lester
    Lester is the given name of Lester B. Pearson, the Canadian diplomat, Nobel Peace Prize laureate, and 14th prime minister of Canada.
  • 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
Triple: [Line 4 Sheppard, connectsStation, Leslie]
Generated description
Leslie is a Toronto subway station on Line 4 Sheppard in the city's transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Leslie
Target entity description: Leslie is a Toronto subway station on Line 4 Sheppard in the city's transit system.
  • A. Leslie
    Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
  • B. Leslie
    Leslie is the given name of Leslie R. Groves Jr., the U.S. Army Corps of Engineers officer who directed the Manhattan Project during World War II.
  • C. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • D. Lester
    Lester is a surname of Irish origin borne by various notable individuals, including the diplomat Seán Lester.
  • E. Lester
    Lester is the given name of Lester B. Pearson, the Canadian diplomat, Nobel Peace Prize laureate, and 14th prime minister of Canada.
  • 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aa9e0f0081909d2a89387d6c08e1 completed March 1, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c00c1db48190906a02bb80fe98dc completed March 4, 2026, 5:15 a.m.
NEDg Description generation batch_69a7c13f15848190b126bdc434953a22 completed March 4, 2026, 5:21 a.m.
NED2 Entity disambiguation (via description) batch_69a7c21dd42881908ac19fed7454d7a9 completed March 4, 2026, 5:24 a.m.
Created at: March 1, 2026, 7:38 p.m.