Triple

T13375819
Position Surface form Disambiguated ID Type / Status
Subject Watertown, Connecticut E319180 entity
Predicate borders P224 FINISHED
Object Thomaston, Connecticut E205397 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: Thomaston, Connecticut | Statement: [Watertown, Connecticut, borders, Thomaston, Connecticut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomaston, Connecticut
Context triple: [Watertown, Connecticut, borders, Thomaston, Connecticut]
  • A. Thomaston, Connecticut chosen
    Thomaston, Connecticut is a small New England town in Litchfield County known for its historic clockmaking industry and traditional downtown.
  • B. Thomaston
    Thomaston is a small incorporated village located on the North Shore of Long Island in Nassau County, New York.
  • C. Thomaston
    Thomaston is a small city in central Georgia, United States, known for its historic downtown and role as a local commercial and cultural hub.
  • D. Thomaston
    Thomaston is a small town located in Marengo County in the state of Alabama, United States.
  • E. Thompson, Connecticut
    Thompson, Connecticut is a small rural town in northeastern Connecticut known for its historic villages and scenic New England character.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadce3fec48190a5443d87c85477a3 completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f72684f3408190952d2619b6b8d241 completed May 3, 2026, 10:42 a.m.
Created at: April 9, 2026, 9:33 p.m.