Triple

T30170237
Position Surface form Disambiguated ID Type / Status
Subject Count of Tendilla E766898 entity
Predicate genderedForm P1805 FINISHED
Object Conde de Tendilla
Conde de Tendilla is a Spanish noble title historically associated with prominent members of the Mendoza family who played key military and political roles, especially during the late Middle Ages and early modern period.
E1920850 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 Tendilla | Statement: [Count of Tendilla, genderedForm, Conde de Tendilla]
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 Tendilla
Triple: [Count of Tendilla, genderedForm, Conde de Tendilla]
Generated description
Conde de Tendilla is a Spanish noble title historically associated with prominent members of the Mendoza family who played key military and political roles, especially during the late Middle Ages and early modern period.

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_69f2247a968881909d79c18f2bfcb275 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67f0b25908190baf7f9dfef6ec6ce completed May 2, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2856da6ee081909b8bfe337b4297d4 completed June 9, 2026, 6:09 p.m.
NEDg Description generation batch_6a28585a2960819096d4e59ad210a0da completed June 9, 2026, 6:15 p.m.
NED2 Entity disambiguation (via description) batch_6a2859680d408190bd5a293365a92f47 completed June 9, 2026, 6:20 p.m.
Created at: April 29, 2026, 7:24 p.m.