Triple

T8083157
Position Surface form Disambiguated ID Type / Status
Subject Munro E188666 entity
Predicate hasVariant P455 FINISHED
Object Monro
Monro is a variant spelling of the Scottish surname Munro, historically associated with a Highland clan from Easter Ross.
 E711142 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: Monro | Statement: [Munro, hasVariant, Monro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Monro
Context triple: [Munro, hasVariant, Monro]
  • A. Peniston
    Peniston is a masculine given name of English origin, historically borne by several members of the British aristocracy.
  • B. Monroe
    Monroe is a Chicago 'L' rapid transit station located in the Loop and served by the Chicago Transit Authority's Red Line.
  • C. Monroe
    Monroe is a surname most famously associated with Earl Monroe, a Hall of Fame American basketball player known for his flashy playing style.
  • D. Monroe
    Monroe is a city in southeastern Michigan known for its location along the River Raisin and its historical significance in the War of 1812.
  • E. Monroe
    Monroe is a mid-sized city in northeastern Louisiana known as a regional hub for commerce, education, and culture along the Ouachita River.
  • 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: Monro
Triple: [Munro, hasVariant, Monro]
Generated description
Monro is a variant spelling of the Scottish surname Munro, historically associated with a Highland clan from Easter Ross.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Monro
Target entity description: Monro is a variant spelling of the Scottish surname Munro, historically associated with a Highland clan from Easter Ross.
  • A. Peniston
    Peniston is a masculine given name of English origin, historically borne by several members of the British aristocracy.
  • B. Monroe
    Monroe is a Chicago 'L' rapid transit station located in the Loop and served by the Chicago Transit Authority's Red Line.
  • C. Monroe
    Monroe is a surname most famously associated with Earl Monroe, a Hall of Fame American basketball player known for his flashy playing style.
  • D. Monroe
    Monroe is a city in southeastern Michigan known for its location along the River Raisin and its historical significance in the War of 1812.
  • E. Monroe
    Monroe is a small city in North Carolina that serves as part of the greater Charlotte metropolitan area.
  • 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_69ca82b662e88190b9323daab8c28a21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb415cb4688190920868317e77bbff completed March 31, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63ff37a88190a980e023a9b7c30c completed April 1, 2026, 12:17 a.m.
NEDg Description generation batch_69cc68634dc88190bc9b9e0598929d4d completed April 1, 2026, 12:35 a.m.
NED2 Entity disambiguation (via description) batch_69cc694d861c8190b504352c1fad2c36 completed April 1, 2026, 12:39 a.m.
Created at: March 30, 2026, 5:28 p.m.