Triple

T21802661
Position Surface form Disambiguated ID Type / Status
Subject CEPT E538274 entity
Predicate abbreviation P43 FINISHED
Object CEPT 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: CEPT | Statement: [CEPT, abbreviation, CEPT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CEPT
Context triple: [CEPT, abbreviation, CEPT]
  • A. CEPT chosen
    CEPT is an Indian university in Ahmedabad renowned for its programs in architecture, planning, design, and related built-environment disciplines.
  • B. CEPT
    CEPT is a European intergovernmental organization that coordinates postal and telecommunications policies and regulations among its member countries.
  • C. CONT
    CONT is the European Parliament’s Committee on Budgetary Control, responsible for overseeing the implementation and proper use of the European Union budget.
  • D. CON
    CON is the stock ticker symbol for Continental AG, a major German automotive parts manufacturer and tire producer.
  • E. CON
    CON is a Nigerian national honor post-nominal indicating a recipient of the Commander of the Order of the Niger.
  • 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_69e0c4733f4081909a86622e7e6d15d2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0780062688190a6c3a2a0364f0f77 completed April 28, 2026, 9:04 a.m.
Created at: April 16, 2026, 6:53 p.m.