Triple

T19856694
Position Surface form Disambiguated ID Type / Status
Subject Bridgewater, Nova Scotia E477149 entity
Predicate locatedInCensusDivision P5151 FINISHED
Object Lunenburg County
Lunenburg County is a coastal county in Nova Scotia, Canada, known for its historic towns, maritime heritage, and scenic Atlantic shoreline.
E1818527 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: Lunenburg County | Statement: [Bridgewater, Nova Scotia, locatedInCensusDivision, Lunenburg County]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lunenburg County
Triple: [Bridgewater, Nova Scotia, locatedInCensusDivision, Lunenburg County]
Generated description
Lunenburg County is a coastal county in Nova Scotia, Canada, known for its historic towns, maritime heritage, and scenic Atlantic shoreline.

Provenance (5 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_69d8e51e7d948190aedbcd6c30361c39 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6586cd8f08190b34c8886e8617255 completed April 20, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16414f88e481909dd63424b18cba70 completed May 27, 2026, 12:56 a.m.
NEDg Description generation batch_6a164212dc348190b4eb5bae50803a5c completed May 27, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_6a16434f165c819081ea70b81354a508 completed May 27, 2026, 1:05 a.m.
Created at: April 10, 2026, 1:51 p.m.