Triple

T28793797
Position Surface form Disambiguated ID Type / Status
Subject Basilica of St. Castor E727030 entity
Predicate namedAfter P63 FINISHED
Object Saint Castor of Karden
Saint Castor of Karden was a 4th-century priest and missionary along the Moselle River, venerated as a Christian saint particularly in the region around Koblenz, Germany.
 E1834097 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 Castor of Karden | Statement: [Basilica of St. Castor, namedAfter, Saint Castor of Karden]
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 Castor of Karden
Triple: [Basilica of St. Castor, namedAfter, Saint Castor of Karden]
Generated description
Saint Castor of Karden was a 4th-century priest and missionary along the Moselle River, venerated as a Christian saint particularly in the region around Koblenz, Germany.

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_69f0319b7c44819085736bcc256185e6 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f6587c26308190a6dce7e40a1eec82 completed May 2, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a2758f6881908880b5599a4bbb4f completed June 6, 2026, 10:43 p.m.
NEDg Description generation batch_6a24a6d6827081909a955a9e55ff5961 completed June 6, 2026, 11:01 p.m.
NED2 Entity disambiguation (via description) batch_6a24aae32fe48190b97460a47a102c47 completed June 6, 2026, 11:18 p.m.
Created at: April 28, 2026, 6:24 a.m.