Triple

T37808758
Position Surface form Disambiguated ID Type / Status
Subject House of Cerda E942576 entity
Predicate notableMember P10 FINISHED
Object Bernardo de la Cerda
Bernardo de la Cerda was a prominent medieval Spanish nobleman of the influential House of Cerda, a cadet branch of the Castilian royal family.
E2255978 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: Bernardo de la Cerda | Statement: [House of Cerda, notableMember, Bernardo de la Cerda]
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: Bernardo de la Cerda
Triple: [House of Cerda, notableMember, Bernardo de la Cerda]
Generated description
Bernardo de la Cerda was a prominent medieval Spanish nobleman of the influential House of Cerda, a cadet branch of the Castilian royal family.

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_69f76ee8104c8190ab17133ccd8f86e6 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbb19b3c9081909cd1c0ab809d6f12 completed May 6, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4167f39cd8819093758c409b7d5518 completed June 28, 2026, 6:29 p.m.
NEDg Description generation batch_6a41687e23248190bc25a3ef8894e8d6 completed June 28, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_6a416af5ea5c819089a00544c3292ba8 completed June 28, 2026, 6:41 p.m.
Created at: May 3, 2026, 4:19 p.m.