Triple

T12142629
Position Surface form Disambiguated ID Type / Status
Subject Siegen E289225 entity
Predicate twinTown P1072 FINISHED
Object Leeds E22344 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: Leeds | Statement: [Siegen, twinTown, Leeds]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leeds
Context triple: [Siegen, twinTown, Leeds]
  • A. Leeds chosen
    Leeds is a major city in West Yorkshire, England, known as a key commercial, cultural, and educational center in the north of the country.
  • B. Sheffield
    Sheffield is a small unincorporated community in West Texas known historically as a ranching and oilfield service town along the Pecos River.
  • C. Sheffield
    Sheffield is a major industrial city in South Yorkshire, England, historically renowned for its steel production and role in the Industrial Revolution.
  • D. Sheffield
    Sheffield is a small rural town in southwestern Massachusetts known for its scenic landscapes, historic charm, and location in the Berkshires.
  • E. Sheffield
    Sheffield is a small town in northern Tasmania, Australia, known as the "Town of Murals" for its numerous outdoor paintings and as a gateway to nearby natural attractions.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915a9838081909622cc14df2a2582 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f64464a48190a2b96e39ab411115 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:49 p.m.