Triple

T14685496
Position Surface form Disambiguated ID Type / Status
Subject Sydney to Canberra Xplorer service E344897 entity
Predicate servesCity P82 FINISHED
Object Sydney E8462 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: Sydney | Statement: [Sydney to Canberra Xplorer service, servesCity, Sydney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sydney
Context triple: [Sydney to Canberra Xplorer service, servesCity, Sydney]
  • A. Sydney
    Sydney is a recurring character in Alison Bechdel’s long-running comic strip "Dykes to Watch Out For," known for her sharp intellect and complex personal relationships within its ensemble cast.
  • B. Sydney chosen
    Sydney is Australia's largest and most populous city, renowned for its iconic harbour, Opera House, and Harbour Bridge.
  • C. Sydney
    Sydney is the spirited, fashionable young woman who serves as the central heroine of Louisa May Alcott’s novel "An Old-Fashioned Girl."
  • D. Sydney
    Sydney is a unisex given name of Old English origin meaning "wide island" that is used in various English-speaking countries.
  • E. Sydney
    Sydney is a character in the British period drama series "Lark Rise to Candleford," which portrays life in two contrasting rural communities in late 19th-century England.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb56bdb8081909ff86440ba20fb1f completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde16c005c81908b54fcfd4243d820 completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:28 a.m.