Triple

T585285
Position Surface form Disambiguated ID Type / Status
Subject Marseille E15143 entity
Predicate timeZone 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: [Marseille, timeZone, CET]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CET
Context triple: [Marseille, timeZone, 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. 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.
  • C. CEST
    CEST is the daylight saving time observed in many Central European countries, typically running one hour ahead of Central European Time.
  • D. ETS
    ETS is a nonprofit organization that develops and administers standardized tests and assessments used worldwide for education, certification, and professional licensing.
  • E. KCET
    KCET is a Los Angeles-based public television station and producer known for creating and distributing influential educational and science programming.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b9874c88190bd1e08d4689ea124 completed March 1, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69a50e25f4e4819081c8973b0f24dec0 completed March 2, 2026, 4:12 a.m.
Created at: March 1, 2026, 7:33 p.m.