Triple

T24480700
Position Surface form Disambiguated ID Type / Status
Subject Bonne Bay E617361 entity
Predicate hasShoreSettlement P16159 FINISHED
Object Lobster Cove
Lobster Cove is a small coastal settlement on the shores of Bonne Bay in Newfoundland and Labrador, Canada, known for its scenic maritime setting and proximity to Gros Morne National Park.
E1638946 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: Lobster Cove | Statement: [Bonne Bay, hasShoreSettlement, Lobster Cove]
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: Lobster Cove
Triple: [Bonne Bay, hasShoreSettlement, Lobster Cove]
Generated description
Lobster Cove is a small coastal settlement on the shores of Bonne Bay in Newfoundland and Labrador, Canada, known for its scenic maritime setting and proximity to Gros Morne National Park.

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_69e2d7f3ae788190b683394db15f220e completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f29ed5d4388190a8a6ce4079aa8a54 completed April 30, 2026, 12:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee7876788190a934cef90090bdf7 completed May 22, 2026, 5:49 a.m.
NEDg Description generation batch_6a0ff03ffa2c81908fe3c321029c784f completed May 22, 2026, 5:57 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff10a3f508190bd92090d91a86020 completed May 22, 2026, 6 a.m.
Created at: April 18, 2026, 2:21 a.m.