Triple

T30948221
Position Surface form Disambiguated ID Type / Status
Subject Madawaska County E788457 entity
Predicate containsParish P38128 FINISHED
Object Saint-François Parish
Saint-François Parish is a civil parish and local administrative division located within Madawaska County in the Canadian province of New Brunswick.
E1944561 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: Saint-François Parish | Statement: [Madawaska County, containsParish, Saint-François Parish]
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: Saint-François Parish
Triple: [Madawaska County, containsParish, Saint-François Parish]
Generated description
Saint-François Parish is a civil parish and local administrative division located within Madawaska County in the Canadian province of New Brunswick.

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_69f224c180f88190ad177372ee02b7e2 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69316b15881908bf0d1c360c217bd completed May 3, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292afc75048190bec5b6e21f7d4a94 completed June 10, 2026, 9:14 a.m.
NEDg Description generation batch_6a292c551da88190bd7637344379983a completed June 10, 2026, 9:20 a.m.
NED2 Entity disambiguation (via description) batch_6a292ce3cc248190a67f29d6334aba40 completed June 10, 2026, 9:22 a.m.
Created at: April 29, 2026, 8:53 p.m.