Triple

T25051265
Position Surface form Disambiguated ID Type / Status
Subject Nájera E627387 entity
Predicate patronSaint P2320 FINISHED
Object Santa María la Real
Santa María la Real is a revered Marian title associated with a historic sanctuary and royal monastery in Nájera, Spain, venerated as the town’s principal religious patron.
E1665168 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: Santa María la Real | Statement: [Nájera, patronSaint, Santa María la Real]
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: Santa María la Real
Triple: [Nájera, patronSaint, Santa María la Real]
Generated description
Santa María la Real is a revered Marian title associated with a historic sanctuary and royal monastery in Nájera, Spain, venerated as the town’s principal religious patron.

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_69e2ff2b4c80819087c916b2b16241b9 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f454a200f481908bceaca32cd1d775 completed May 1, 2026, 7:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105ce77d348190b7772e56a09d8836 completed May 22, 2026, 1:40 p.m.
NEDg Description generation batch_6a105daad81481909d399aba96a1176c completed May 22, 2026, 1:44 p.m.
NED2 Entity disambiguation (via description) batch_6a105e3d647881909b04575cd240d468 completed May 22, 2026, 1:46 p.m.
Created at: April 18, 2026, 6:09 a.m.