Triple

T846403
Position Surface form Disambiguated ID Type / Status
Subject Lille E18284 entity
Predicate twinnedWith P1072 FINISHED
Object Essex County E30848 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: Essex County | Statement: [Lille, twinnedWith, Essex County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Essex County
Context triple: [Lille, twinnedWith, Essex County]
  • A. Essex County
    Essex County is a historic coastal county in northeastern Massachusetts that includes cities such as Lynn, Salem, and Lawrence.
  • B. Middlesex County
    Middlesex County is a populous county in central New Jersey known for its diverse suburban communities, major transportation hubs, and proximity to New York City.
  • C. Suffolk County
    Suffolk County is an urban county in eastern Massachusetts that includes the city of Boston and serves as a major political, economic, and cultural hub of the state.
  • D. Essex County, New Jersey
    Essex County, New Jersey is a densely populated county in the northeastern part of the state that includes major urban centers like Newark and is part of the New York metropolitan area.
  • E. Essex chosen
    Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
  • 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_69a4938b04208190b82e1df6b572c548 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac0a91e48190b4349ae8bb67fd90 completed March 1, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4bfac5cc8190a5fba1c5da98391d completed March 7, 2026, 4:02 p.m.
Created at: March 1, 2026, 7:38 p.m.