Triple

T16913836
Position Surface form Disambiguated ID Type / Status
Subject LKPR E410270 entity
Predicate timeZoneStandard P109 FINISHED
Object CET E5929 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: CET | Statement: [LKPR, timeZoneStandard, CET]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CET
Context triple: [LKPR, timeZoneStandard, CET]
  • A. CET chosen
    CET is the standard time zone used by many countries in central Europe, typically one hour ahead of Coordinated Universal Time (UTC+1).
  • B. CETS
    CETS is the standard abbreviation for the Council of Europe’s official treaty publication series, which compiles and numbers all conventions and agreements concluded within the organization.
  • C. GCET
    GCET is an internationally recognized framework established by the UN World Tourism Organization that sets out principles to promote responsible, sustainable, and universally accessible tourism.
  • D. CUET
    CUET is a leading public engineering university in Bangladesh located in Chittagong, specializing in engineering, technology, and architecture education and research.
  • E. Test of English as a Foreign Language
    The Test of English as a Foreign Language (TOEFL) is a standardized exam that measures the English language proficiency of non-native speakers for academic and professional purposes, especially for admission to universities in English-speaking countries.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3ca3f1a2c8190a512ccc09a080eb4 completed April 18, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7be679c8190b9d0b0b9cfe185d3 completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:30 a.m.