Triple

T25152193
Position Surface form Disambiguated ID Type / Status
Subject Palo del Colle E630106 entity
Predicate hasSaint P8397 FINISHED
Object San Vincenzo Ferreri
San Vincenzo Ferreri, known in English as Saint Vincent Ferrer, was a 14th–15th century Spanish Dominican friar and renowned preacher venerated as a Catholic saint.
E1696809 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: San Vincenzo Ferreri | Statement: [Palo del Colle, hasSaint, San Vincenzo Ferreri]
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: San Vincenzo Ferreri
Triple: [Palo del Colle, hasSaint, San Vincenzo Ferreri]
Generated description
San Vincenzo Ferreri, known in English as Saint Vincent Ferrer, was a 14th–15th century Spanish Dominican friar and renowned preacher venerated as a Catholic saint.

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_69e2ff349e408190a6f4a5a66279f54d completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f46b8404a48190a654528935d0f07d completed May 1, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10d9dfe3d481909614b434a117aacb completed May 22, 2026, 10:34 p.m.
NEDg Description generation batch_6a10dadc94ac819093dcd582156e6705 completed May 22, 2026, 10:38 p.m.
NED2 Entity disambiguation (via description) batch_6a10db3bac4c81908662fb96783d2612 completed May 22, 2026, 10:39 p.m.
Created at: April 18, 2026, 6:30 a.m.