Triple

T620494
Position Surface form Disambiguated ID Type / Status
Subject SIGCSE E14500 entity
Predicate abbreviation P43 FINISHED
Object SIGCSE E14500 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: SIGCSE | Statement: [SIGCSE, abbreviation, SIGCSE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SIGCSE
Context triple: [SIGCSE, abbreviation, SIGCSE]
  • A. SIGCSE chosen
    SIGCSE is a leading ACM special interest group focused on computer science education, supporting educators through conferences, publications, and community initiatives.
  • B. SIGPLAN
    SIGPLAN is the ACM Special Interest Group on Programming Languages, focusing on research, development, and education in programming language design and implementation.
  • C. SIGSOFT
    SIGSOFT is the ACM Special Interest Group on Software Engineering, focusing on advancing research, education, and practice in software engineering.
  • D. SIGCHI
    SIGCHI is the ACM Special Interest Group on Computer-Human Interaction, a leading professional community focused on advancing research and practice in human-computer interaction.
  • E. International Conference on Software Engineering
    The International Conference on Software Engineering is a premier annual academic and industry forum for presenting and discussing cutting-edge research, practices, and innovations in software engineering.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e270b448190beb677670443b5b6 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a563c682f88190a2af1087246be4c4 completed March 2, 2026, 10:17 a.m.
Created at: March 1, 2026, 7:35 p.m.