Triple

T26401312
Position Surface form Disambiguated ID Type / Status
Subject Saint-Junien E663705 entity
Predicate namedAfter P63 FINISHED
Object Saint Junian of Nontron
Saint Junian of Nontron was a 6th-century Christian hermit and abbot from the Périgord region of France, venerated as a local saint and patron associated with the town of Saint-Junien.
E1724203 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 Junian of Nontron | Statement: [Saint-Junien, namedAfter, Saint Junian of Nontron]
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 Junian of Nontron
Triple: [Saint-Junien, namedAfter, Saint Junian of Nontron]
Generated description
Saint Junian of Nontron was a 6th-century Christian hermit and abbot from the Périgord region of France, venerated as a local saint and patron associated with the town of Saint-Junien.

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_69ee883823988190b418b111be28a44a completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f610f493188190aea2bf6268995310 completed May 2, 2026, 2:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aeb65f088190b150fae1f0939f65 completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11afb54ae8819080879d203d92a5c9 completed May 23, 2026, 1:46 p.m.
NED2 Entity disambiguation (via description) batch_6a11b051d328819090f947755dda4cfc completed May 23, 2026, 1:49 p.m.
Created at: April 26, 2026, 11:32 p.m.