Triple

T7397776
Position Surface form Disambiguated ID Type / Status
Subject Nack the duckling E170665 entity
Predicate hasLanguageOfWorkOrName P15 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: [Nack the duckling, hasLanguageOfWorkOrName, English]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: English
Context triple: [Nack the duckling, hasLanguageOfWorkOrName, 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_69c68a5f04188190ac266569c9280347 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f24abcd08190b8428fa22b2fbd4f completed March 27, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81106c0788190a3740acf7bb4ab86 completed March 28, 2026, 5:33 p.m.
Created at: March 27, 2026, 3:09 p.m.