Triple

T1563051
Position Surface form Disambiguated ID Type / Status
Subject Lasell University E33370 entity
Predicate mascot P52 FINISHED
Object Laser
Laser is the costumed mascot representing Lasell University at its athletic events and campus activities.
 E177577 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: Laser | Statement: [Lasell University, mascot, Laser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Laser
Context triple: [Lasell University, mascot, Laser]
  • A. Maser
    Maser is a small town in the Veneto region of northern Italy, noted for its Renaissance architecture and association with the architect Andrea Palladio.
  • B. Turbostar
    Turbostar is a family of modern British diesel multiple-unit trains widely used for regional and commuter services across the UK rail network.
  • C. Blisk
    Blisk is a fictional setting or universe in which the character or concept known as Blink appears or is utilized.
  • D. Opti
    Opti is a friendly, futuristic robot character that served as one of the official mascots of Expo 2020 Dubai.
  • E. Luma
    Luma is a small, star-shaped celestial creature from the Super Mario series, known for its cute appearance and connection to Rosalina and the cosmos.
  • 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: Laser
Triple: [Lasell University, mascot, Laser]
Generated description
Laser is the costumed mascot representing Lasell University at its athletic events and campus activities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Laser
Target entity description: Laser is the costumed mascot representing Lasell University at its athletic events and campus activities.
  • A. Maser
    Maser is a small town in the Veneto region of northern Italy, noted for its Renaissance architecture and association with the architect Andrea Palladio.
  • B. Turbostar
    Turbostar is a family of modern British diesel multiple-unit trains widely used for regional and commuter services across the UK rail network.
  • C. Blisk
    Blisk is a fictional setting or universe in which the character or concept known as Blink appears or is utilized.
  • D. Opti
    Opti is a friendly, futuristic robot character that served as one of the official mascots of Expo 2020 Dubai.
  • E. Luma
    Luma is a small, star-shaped celestial creature from the Super Mario series, known for its cute appearance and connection to Rosalina and the cosmos.
  • 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_69a885ef9cf48190b0af0f5ce3d02231 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908886efc8190a630ef1e06d0d9cb completed March 5, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad3717a9a08190b3d997bb7bc6e14f completed March 8, 2026, 8:45 a.m.
NEDg Description generation batch_69ad37e306948190bbaa14829ce094e6 completed March 8, 2026, 8:48 a.m.
NED2 Entity disambiguation (via description) batch_69ad38d106348190835d753c6cffcc48 completed March 8, 2026, 8:52 a.m.
Created at: March 4, 2026, 7:27 p.m.