Triple

T25051242
Position Surface form Disambiguated ID Type / Status
Subject Nájera E627387 entity
Predicate notableFor P22 FINISHED
Object Royal Pantheon of Navarrese kings
The Royal Pantheon of Navarrese kings is a historic burial site in Nájera, Spain, where numerous medieval monarchs of the Kingdom of Navarre are interred.
E1664670 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: Royal Pantheon of Navarrese kings | Statement: [Nájera, notableFor, Royal Pantheon of Navarrese kings]
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: Royal Pantheon of Navarrese kings
Triple: [Nájera, notableFor, Royal Pantheon of Navarrese kings]
Generated description
The Royal Pantheon of Navarrese kings is a historic burial site in Nájera, Spain, where numerous medieval monarchs of the Kingdom of Navarre are interred.

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_6a1048c9f0508190b3d10208b112016b completed May 22, 2026, 12:15 p.m.
NEDg Description generation batch_6a104cbac0b48190ac739e35c090180f completed May 22, 2026, 12:31 p.m.
NED2 Entity disambiguation (via description) batch_6a104d2be4f08190a7a94bc1b04223cf completed May 22, 2026, 12:33 p.m.
Created at: April 18, 2026, 6:09 a.m.