Triple

T356454
Position Surface form Disambiguated ID Type / Status
Subject Lynn Harbor E7552 entity
Predicate near P350 FINISHED
Object Revere, Massachusetts E8138 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: Revere, Massachusetts | Statement: [Lynn Harbor, near, Revere, Massachusetts]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Revere, Massachusetts
Context triple: [Lynn Harbor, near, Revere, Massachusetts]
  • A. Revere, Massachusetts chosen
    Revere, Massachusetts is a coastal city just north of Boston known for Revere Beach, the oldest public beach in the United States.
  • B. Stoneham, Massachusetts
    Stoneham, Massachusetts is a suburban town north of Boston known for its residential character and proximity to the Middlesex Fells Reservation.
  • C. Malden, Massachusetts
    Malden, Massachusetts is a suburban city just north of Boston known for its diverse population, historic neighborhoods, and mix of residential and commercial areas.
  • D. Boston Common
    Boston Common is a historic central public park in downtown Boston and the oldest city park in the United States.
  • E. Lowell, Massachusetts
    Lowell, Massachusetts is a historic New England city known as a cradle of the American Industrial Revolution and a center of early textile manufacturing.
  • 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_69a2e7e696948190bebc966535995e45 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebaf0c9881909313f98818e7fa58 completed Feb. 28, 2026, 1:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd4620c7c81909e30a2dfd55602fb completed March 8, 2026, 1:44 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.