Triple

T230481
Position Surface form Disambiguated ID Type / Status
Subject Mitchell Kapor E4399 entity
Predicate notableWork P4 FINISHED
Object Lotus 1-2-3 E29574 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: Lotus 1-2-3 | Statement: [Mitchell Kapor, notableWork, Lotus 1-2-3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lotus 1-2-3
Context triple: [Mitchell Kapor, notableWork, Lotus 1-2-3]
  • A. Lotus 1-2-3 chosen
    Lotus 1-2-3 is a pioneering spreadsheet software program for personal computers that became a dominant business application in the 1980s.
  • B. Lotus Notes
    Lotus Notes is a collaborative client-server software platform best known for its email, calendaring, and business application capabilities, widely used in enterprises for groupware and workflow solutions.
  • C. Tableau
    Tableau is a widely used data visualization and business intelligence software platform that enables users to analyze, explore, and present data through interactive dashboards and reports.
  • D. IBM PC
    The IBM PC is the original 1981 personal computer model from IBM that became a de facto industry standard and helped popularize home and business computing worldwide.
  • E. Micros Systems
    Micros Systems was a leading provider of point-of-sale and hospitality management software and hardware solutions for restaurants, hotels, and retail 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_69a257363ffc81909757bde7ab3404da completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25cac7994819080b0b3b10808f8e5 completed Feb. 28, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69a362bd591c8190940e6b1cd81017ae completed Feb. 28, 2026, 9:48 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.