Triple

T1263
Position Surface form Disambiguated ID Type / Status
Subject oN-Line System E25 entity
Predicate alsoKnownAs P39 FINISHED
Object NLS E25 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: NLS | Statement: [oN-Line System, alsoKnownAs, NLS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NLS
Context triple: [oN-Line System, alsoKnownAs, NLS]
  • A. Veritas
    Veritas is the Latin word for "truth" and is famously used as the motto of Harvard University.
  • B. Douglas
    Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
  • C. NACA
    NACA (the National Advisory Committee for Aeronautics) was the U.S. government agency that conducted pioneering aeronautical research and served as the predecessor to NASA.
  • D. oN-Line System chosen
    The oN-Line System (NLS) was an early, pioneering computer system that introduced many foundational concepts of modern computing, including the mouse, hypertext, and interactive graphical user interfaces.
  • E. Tymshare
    Tymshare was an influential American time-sharing and computer services company active in the 1960s–1980s that helped pioneer remote computing and software services for businesses.
  • 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_69a22a285828819081a58308fb963df1 completed Feb. 27, 2026, 11:35 p.m.
NER Named-entity recognition batch_69a230c560548190a57df2421e233775 completed Feb. 28, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69a238e0dd0c8190999b824f8f32b9d0 completed Feb. 28, 2026, 12:37 a.m.
Created at: Feb. 27, 2026, 11:36 p.m.