Triple

T22566039
Position Surface form Disambiguated ID Type / Status
Subject Career Education Corporation E557952 entity
Predicate listedAs P310 FINISHED
Object CECO 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: CECO | Statement: [Career Education Corporation, listedAs, CECO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CECO
Context triple: [Career Education Corporation, listedAs, CECO]
  • A. CECO chosen
    CECO is the stock ticker symbol for Career Education Corporation, a U.S.-based provider of postsecondary education and career-focused training programs.
  • B. COMCO
    COMCO is the Swiss Competition Commission, the federal authority responsible for enforcing antitrust and competition law in Switzerland.
  • C. CE&C
    CE&C is the commonly used abbreviation for the Department of Chemical Engineering and Chemistry, an academic unit focused on education and research in chemical engineering and chemistry.
  • D. JECO
    JECO is a Japanese consortium that holds an ownership stake in Chile’s Escondida copper mine.
  • E. SEMCO
    SEMCO is the brand name used by Samsung Electro-Mechanics for its electronic components and related technologies.
  • 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_69e11e5ae4ac8190b1f503457603d969 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15fa9ebc8819098d74fb41e14bd7e completed April 29, 2026, 1:32 a.m.
Created at: April 16, 2026, 8:52 p.m.