Triple

T26635841
Position Surface form Disambiguated ID Type / Status
Subject Palacio del Conde de Santovenia E668632 entity
Predicate namedAfter P63 FINISHED
Object Conde de Santovenia
Conde de Santovenia was a Spanish noble title associated with an aristocrat whose name was given to the historic Palacio del Conde de Santovenia.
E1735174 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: Conde de Santovenia | Statement: [Palacio del Conde de Santovenia, namedAfter, Conde de Santovenia]
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: Conde de Santovenia
Triple: [Palacio del Conde de Santovenia, namedAfter, Conde de Santovenia]
Generated description
Conde de Santovenia was a Spanish noble title associated with an aristocrat whose name was given to the historic Palacio del Conde de Santovenia.

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_69ee9d0024b8819090a7c8cf669a3b6c completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f616298eb48190913aefb29005cd67 completed May 2, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec3a6a388190a46048dbe6564a4d completed May 23, 2026, 6:04 p.m.
NEDg Description generation batch_6a11ed8f691081908dc4eeb38b8a56cd completed May 23, 2026, 6:10 p.m.
NED2 Entity disambiguation (via description) batch_6a11ee308af88190b08944270a2fd1d8 completed May 23, 2026, 6:13 p.m.
Created at: April 27, 2026, 2:27 a.m.