Triple

T22330662
Position Surface form Disambiguated ID Type / Status
Subject PEP 333 E552012 entity
Predicate relatedTo P37 FINISHED
Object CGI NE NERFINISHED

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: CGI | Statement: [PEP 333, relatedTo, CGI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CGI
Context triple: [PEP 333, relatedTo, CGI]
  • A. CGI chosen
    CGI is a standard protocol that enables web servers to execute external programs and dynamically generate web content in response to user requests.
  • B. CGI
    CGI is a high-contrast Coronagraph Instrument designed to directly image and study exoplanets and circumstellar disks by blocking out starlight.
  • C. CGI
    CGI (computer-generated imagery) is the creation of still or animated visual content using computer software, widely used in film, television, video games, and advertising for visual effects and digital environments.
  • D. Cg
    Cg is a high-level shading language developed by NVIDIA for programming graphics processing units, similar in design and purpose to HLSL.
  • E. CGA
    CGA is the abbreviated name commonly used for Taiwan’s Coast Guard Administration, the maritime law enforcement and search-and-rescue agency.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e482f788190b78d1588fc26d606 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1577a9c348190b8662142afa832be completed April 29, 2026, 12:57 a.m.
Created at: April 16, 2026, 8:43 p.m.