Triple

T9526774
Position Surface form Disambiguated ID Type / Status
Subject CCEO E229777 entity
Predicate hasCanonicalAbbreviation P8075 FINISHED
Object CCEO E229777 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: CCEO | Statement: [CCEO, hasCanonicalAbbreviation, CCEO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CCEO
Context triple: [CCEO, hasCanonicalAbbreviation, CCEO]
  • A. CCEO chosen
    CCEO is the commonly used abbreviation for the Code of Canons of the Eastern Churches, the body of canon law governing the Eastern Catholic Churches.
  • B. CCE
    CCE is a division at the California Institute of Technology focused on research and education in chemistry and chemical engineering.
  • C. CCE
    CCE is an abbreviation commonly used for the Center for Civic Engagement, an organization that promotes community involvement, public service, and civic responsibility.
  • D. CCO
    CCO is the FAA location identifier for Newnan–Coweta County Airport in Georgia, United States.
  • E. CECO
    CECO is the stock ticker symbol for Career Education Corporation, a U.S.-based provider of postsecondary education and career-focused training programs.
  • 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_69ca8479934c81908006d0e6e970ae05 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd989c831081908877e42f7ead84ba completed April 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c2710b481909a13d946f6dd5b2d completed April 4, 2026, 5:36 p.m.
Created at: March 30, 2026, 8 p.m.