Triple

T18813349
Position Surface form Disambiguated ID Type / Status
Subject Halifax Harbour E460069 entity
Predicate adjacentTo P224 FINISHED
Object Georges Island
Georges Island is a small fortified island in Halifax Harbour, Nova Scotia, known for its historic military installations and role in coastal defense.
E2283189 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: Georges Island | Statement: [Halifax Harbour, adjacentTo, Georges Island]
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: Georges Island
Triple: [Halifax Harbour, adjacentTo, Georges Island]
Generated description
Georges Island is a small fortified island in Halifax Harbour, Nova Scotia, known for its historic military installations and role in coastal defense.

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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a3de2f6881908a9da4d5abd7ee61 completed April 20, 2026, 3:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a42458aae7c8190bc0e52176a4f6157 completed June 29, 2026, 10:14 a.m.
NEDg Description generation batch_6a42464ca16481908e1995aad6db4aaf completed June 29, 2026, 10:17 a.m.
NED2 Entity disambiguation (via description) batch_6a4246ecd70081908fc2cb7db04210b1 completed June 29, 2026, 10:20 a.m.
Created at: April 10, 2026, 11:53 a.m.