Triple

T574765
Position Surface form Disambiguated ID Type / Status
Subject SIGCAS E13738 entity
Predicate acronym P43 FINISHED
Object SIGCAS E13738 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: SIGCAS | Statement: [SIGCAS, acronym, SIGCAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SIGCAS
Context triple: [SIGCAS, acronym, SIGCAS]
  • A. SIGCAS chosen
    SIGCAS is the ACM Special Interest Group on Computers and Society, focusing on the social, ethical, and policy implications of computing technologies.
  • B. ISCAS
    ISCAS is a premier annual IEEE conference focused on research and innovation in circuits, systems, and related technologies.
  • C. 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.
  • D. SIGCSE
    SIGCSE is a leading ACM special interest group focused on computer science education, supporting educators through conferences, publications, and community initiatives.
  • E. SIGSOFT
    SIGSOFT is the ACM Special Interest Group on Software Engineering, focusing on advancing research, education, and practice 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_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_69a4ff4c3df48190a886a8d3c633d417 completed March 2, 2026, 3:09 a.m.
Created at: March 1, 2026, 7:33 p.m.