Triple

T14826401
Position Surface form Disambiguated ID Type / Status
Subject Forbes Shire E348585 entity
Predicate containsTown P847 FINISHED
Object Forbes E69893 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: Forbes | Statement: [Forbes Shire, containsTown, Forbes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Forbes
Context triple: [Forbes Shire, containsTown, Forbes]
  • A. Forbes
    Forbes is a global media company best known for its business magazine that ranks and profiles the world’s wealthiest individuals, companies, and influential leaders.
  • B. Forbes chosen
    Forbes is a historic rural town in central-west New South Wales, Australia, known for its agricultural industry and heritage architecture along the Lachlan River.
  • C. Fortune magazine
    Fortune magazine is a prominent American business publication known for its in-depth reporting on corporate affairs, economics, and its influential rankings such as the Fortune 500.
  • D. Forbes Border Post
    Forbes Border Post is a key road border crossing between Zimbabwe and Mozambique located near the city of Mutare in eastern Zimbabwe.
  • E. The Wall Street Journal
    The Wall Street Journal is a leading American business-focused daily newspaper known for its influential financial reporting and analysis.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded0713700819097bbb0352650984b completed April 14, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe64fab7bc8190af55cc6ec5eafb65 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:51 a.m.