Triple

T17339037
Position Surface form Disambiguated ID Type / Status
Subject Ten Cities That Made an Empire E421015 entity
Predicate hasPart P35 FINISHED
Object Melbourne NE NERFINISHED

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: Melbourne | Statement: [Ten Cities That Made an Empire, hasPart, Melbourne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melbourne
Context triple: [Ten Cities That Made an Empire, hasPart, Melbourne]
  • A. Melbourne
    Melbourne is a coastal city in east-central Florida known for its beaches, aerospace and technology industries, and role as a commercial and cultural hub of the Space Coast.
  • B. Melbourne
    "Melbourne" is a 2014 Iranian drama film directed by Nima Javidi, known for its tense, character-driven story about a young couple facing a moral crisis on the day they plan to emigrate.
  • C. Melbourne chosen
    Melbourne is a major Australian city known for its vibrant arts scene, diverse culture, and status as a leading center for sports and education.
  • D. Melbourne
    Melbourne is a historic market town in Derbyshire, England, known for its Georgian architecture and the notable Melbourne Hall and gardens.
  • E. Melbourn
    Melbourn is a village and civil parish in South Cambridgeshire, England, known for its historic architecture and rural community character.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889d3adc881909319f1edb8d2a956 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a13dd44819091d296c764976dfe completed April 19, 2026, 2:12 a.m.
Created at: April 10, 2026, 5:44 a.m.