Triple

T38148501
Position Surface form Disambiguated ID Type / Status
Subject Muniadona of Castile E952686 entity
Predicate child P120 FINISHED
Object Gonzalo Sánchez
Gonzalo Sánchez was a medieval Iberian nobleman, likely a lesser-known son within the Castilian-Leonese royal lineage connected to the house of Muniadona of Castile.
E2281687 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: Gonzalo Sánchez | Statement: [Muniadona of Castile, child, Gonzalo Sánchez]
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: Gonzalo Sánchez
Triple: [Muniadona of Castile, child, Gonzalo Sánchez]
Generated description
Gonzalo Sánchez was a medieval Iberian nobleman, likely a lesser-known son within the Castilian-Leonese royal lineage connected to the house of Muniadona of Castile.

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_69f76f0a67f4819080c492f61d688fcc completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc462d13d08190a90114f40dd4b25a completed May 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a4205aa363c8190acf18e6876138b03 completed June 29, 2026, 5:42 a.m.
NEDg Description generation batch_6a4207c8ee00819085ecd854f97b632f completed June 29, 2026, 5:51 a.m.
NED2 Entity disambiguation (via description) batch_6a420900d9188190bb1626851114e1ce completed June 29, 2026, 5:56 a.m.
Created at: May 3, 2026, 4:21 p.m.