Triple

T574857
Position Surface form Disambiguated ID Type / Status
Subject ACM SIGAPP E13740 entity
Predicate hasAcronym P43 FINISHED
Object SIGAPP E2477 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: SIGAPP | Statement: [ACM SIGAPP, hasAcronym, SIGAPP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SIGAPP
Context triple: [ACM SIGAPP, hasAcronym, SIGAPP]
  • A. SIG chosen
    SIG is an acronym commonly used by the Association for Computing Machinery to denote its specialized Special Interest Groups that focus on particular areas of computing research and practice.
  • B. Syl Apps
    Syl Apps was a Canadian professional ice hockey centre and Hall of Famer best known as a star player for the Toronto Maple Leafs in the 1930s and 1940s.
  • C. Qsuite
    Qsuite is Qatar Airways’ premium business-class suite product featuring enclosed seats with doors, lie-flat beds, and customizable configurations for enhanced privacy and comfort.
  • D. AppDynamics
    AppDynamics is an application performance monitoring and observability company that provides tools to track, analyze, and optimize the performance of software applications and IT infrastructure.
  • E. Siebel
    Siebel is a surname most prominently associated with Jennifer Siebel Newsom, an American documentary filmmaker and the First Partner of California.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b4c23548190a3b883239c7c78c8 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a501bfb6408190bf7e1f462f39723d completed March 2, 2026, 3:19 a.m.
Created at: March 1, 2026, 7:33 p.m.