Triple

T615786
Position Surface form Disambiguated ID Type / Status
Subject Apple Lisa E14399 entity
Predicate bundledSoftware P1593 FINISHED
Object LisaProject
LisaProject was a project management and scheduling application included with Apple's Lisa computer system, designed to help users plan and track tasks and timelines.
 E77077 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: LisaProject | Statement: [Apple Lisa, bundledSoftware, LisaProject]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LisaProject
Context triple: [Apple Lisa, bundledSoftware, LisaProject]
  • A. Sloan
    Sloan is a surname most notably associated with Alfred P. Sloan, the influential long-time president and chairman of General Motors.
  • B. Jacobs
    Jacobs is a surname most notably associated with Harriet Jacobs, the African-American writer and abolitionist who authored the influential slave narrative "Incidents in the Life of a Slave Girl."
  • C. Lee
    Lee is a given name shared by numerous individuals across different cultures and professions.
  • D. Linda
    Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
  • E. Luce
    Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
  • 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: LisaProject
Triple: [Apple Lisa, bundledSoftware, LisaProject]
Generated description
LisaProject was a project management and scheduling application included with Apple's Lisa computer system, designed to help users plan and track tasks and timelines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LisaProject
Target entity description: LisaProject was a project management and scheduling application included with Apple's Lisa computer system, designed to help users plan and track tasks and timelines.
  • A. Sloan
    Sloan is a surname most notably associated with Alfred P. Sloan, the influential long-time president and chairman of General Motors.
  • B. Jacobs
    Jacobs is a surname most notably associated with Harriet Jacobs, the African-American writer and abolitionist who authored the influential slave narrative "Incidents in the Life of a Slave Girl."
  • C. Lee
    Lee is a given name shared by numerous individuals across different cultures and professions.
  • D. Linda
    Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
  • E. Luce
    Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e0b438881909ad515adf7a4eb79 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5554b4f888190b9b64ece37087bf4 completed March 2, 2026, 9:15 a.m.
NEDg Description generation batch_69a555ae08b88190aad64ec7923437ef completed March 2, 2026, 9:17 a.m.
NED2 Entity disambiguation (via description) batch_69a556669878819098816d2221a3fd3d completed March 2, 2026, 9:20 a.m.
Created at: March 1, 2026, 7:35 p.m.