Triple

T4082369
Position Surface form Disambiguated ID Type / Status
Subject Massachusetts Route 24 E87504 entity
Predicate passesThrough P225 FINISHED
Object Berkley E160237 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: Berkley | Statement: [Massachusetts Route 24, passesThrough, Berkley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berkley
Context triple: [Massachusetts Route 24, passesThrough, Berkley]
  • A. Berkley chosen
    Berkley is a small rural town in Bristol County, Massachusetts, known for its quiet residential character and proximity to the Taunton River.
  • B. Berkley, Michigan
    Berkley, Michigan is a small suburban city in Oakland County known for its tree-lined neighborhoods, family-friendly community, and proximity to Detroit.
  • C. Everett
    Everett is a city in Middlesex County, Massachusetts, located just north of Boston and known for its industrial history and urban residential character.
  • D. Everett
    Everett is a surname of English origin borne by various notable individuals, including American politician and orator Edward Everett.
  • E. Everett
    Everett is a city in western Washington State, known as a major industrial and maritime hub north of Seattle and home to a large Boeing aircraft assembly plant.
  • 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_69aed9435cf48190ad1da737c962d19d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc77dab481909bcf197daf2def59 completed March 9, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562c3e1b081908cd783d9399a751f completed March 14, 2026, 1:29 p.m.
Created at: March 9, 2026, 3:39 p.m.