Triple

T3636407
Position Surface form Disambiguated ID Type / Status
Subject LisaTerminal E77078 entity
Predicate operatingSystem P1593 FINISHED
Object Lisa OS E77071 NE FINISHED

How this triple was built (2 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: Lisa OS | Statement: [LisaTerminal, operatingSystem, Lisa OS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisa OS
Context triple: [LisaTerminal, operatingSystem, Lisa OS]
  • A. Lisa OS chosen
    Lisa OS was the graphical user interface–based operating system developed by Apple for its early Lisa personal computer, notable for pioneering features like overlapping windows, menus, and a mouse-driven desktop.
  • B. LILO
    LILO is a classic Linux bootloader that was widely used on early Linux distributions to load operating systems at startup.
  • C. Lanman
    Lanman is a surname most notably associated with American philanthropist William K. Lanman Jr., a major benefactor of Yale University.
  • D. Lisa
    Lisa is a feminine given name commonly used in English-speaking countries, often as a shortened form of Elizabeth or Melissa.
  • E. Lisa
    Lisa is the given name of Australian musician and composer Lisa Gerrard, renowned for her work as part of Dead Can Dance and for her film scores.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad85dd0be48190b738990cb20c4731 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc3278bb8819098bbeac023410111 completed March 8, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44f1ec2bc8190ae88a2010f84e998 completed March 13, 2026, 5:53 p.m.
Created at: March 8, 2026, 3:24 p.m.