Triple

T15616146
Position Surface form Disambiguated ID Type / Status
Subject Lisa File System E375415 entity
Predicate usedWith P4791 FINISHED
Object LisaTerminal E77078 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: LisaTerminal | Statement: [Lisa File System, usedWith, LisaTerminal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LisaTerminal
Context triple: [Lisa File System, usedWith, LisaTerminal]
  • A. LisaTerminal chosen
    LisaTerminal was a terminal emulation application for the Apple Lisa that allowed the computer to connect to and interact with remote mainframes and minicomputers.
  • B. Terminal
    Terminal is the built-in command-line interface application for macOS that allows users to interact with the operating system using text-based commands.
  • C. Terminal
    Terminal is a 2018 neo-noir thriller film starring Margot Robbie, known for its stylized visuals and dark, twisting narrative.
  • D. Terminal
    Terminal is a popular multiplayer map in Call of Duty: Modern Warfare 2 set in a modern airport environment featuring tight indoor spaces and open tarmac areas.
  • E. Terminal C (former)
    Terminal C (former) was a now-closed passenger terminal at Kansas City International Airport that once served as one of its primary concourses for airline operations.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e980b748190b43c0b650bf1e629 completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56dd1e4c819090bf3cd4425b39b7 completed May 9, 2026, 3:46 p.m.
Created at: April 10, 2026, 4:13 a.m.