Triple

T19452731
Position Surface form Disambiguated ID Type / Status
Subject Federal Correctional Institution, Danbury E486651 entity
Predicate city P40 FINISHED
Object Danbury 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: Danbury | Statement: [Federal Correctional Institution, Danbury, city, Danbury]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danbury
Context triple: [Federal Correctional Institution, Danbury, city, Danbury]
  • A. Danbury, Connecticut chosen
    Danbury, Connecticut is a city in western Connecticut known historically for its hat-making industry and as a regional commercial and cultural center.
  • B. Waterbury
    Waterbury is a small Vermont town known for its scenic Green Mountain setting, outdoor recreation, and attractions like the Ben & Jerry’s ice cream factory.
  • C. Waterbury
    Waterbury is a historic industrial city in western Connecticut known for its former prominence in brass manufacturing and its nickname "The Brass City."
  • D. Naugatuck
    Naugatuck is a borough and town in Connecticut known for its industrial history and location along the Naugatuck River.
  • E. Meriden
    Meriden is a village and civil parish in the West Midlands of England, historically known as a traditional contender for the geographical centre of England.
  • 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6339407a08190a3e0213bfbb4df3d completed April 20, 2026, 2:09 p.m.
Created at: April 10, 2026, 1:38 p.m.