Triple

T8204470
Position Surface form Disambiguated ID Type / Status
Subject Commission for Basic Systems E191654 entity
Predicate usesOfficialLanguage P236 FINISHED
Object English E211 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: English | Statement: [Commission for Basic Systems, usesOfficialLanguage, English]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: English
Context triple: [Commission for Basic Systems, usesOfficialLanguage, English]
  • A. English chosen
    English is a widely spoken West Germanic language that serves as a global lingua franca in education, business, science, and international communication.
  • B. ENG
    ENG is the three-letter FIFA country code used to represent the England national football team in international competitions and official records.
  • C. EN
    EN is the standard abbreviation used in Portugal for "Estrada Nacional," the national road network.
  • D. Angolalla
    Angolalla is a historic town in central Ethiopia known as the birthplace of Emperor Menelik II.
  • E. World English
    World English is a phonetic notation system developed by Alexander Melville Bell to represent the sounds of spoken English with precision.
  • 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_69ca82c7f3e08190857bf1fc63b2a10c completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb7268e2dc8190b630ea2bb75d0474 completed March 31, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccedd27bc08190a8109217069a8978 completed April 1, 2026, 10:05 a.m.
Created at: March 30, 2026, 5:43 p.m.