Triple

T12264096
Position Surface form Disambiguated ID Type / Status
Subject Pepita Tudó E292297 entity
Predicate familyName P18 FINISHED
Object Tudó
Tudó is the surname of Pepita Tudó, a Spanish woman historically known as the mistress of Manuel de Godoy, a powerful statesman in late 18th- and early 19th-century Spain.
 E971231 NE FINISHED

How this triple was built (4 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: Tudó | Statement: [Pepita Tudó, familyName, Tudó]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tudó
Context triple: [Pepita Tudó, familyName, Tudó]
  • A. Tuder
    Tuder was an important ancient Umbrian settlement in central Italy, known today as the hilltop town of Todi.
  • B. Taznatit
    Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
  • C. Tumshuq
    Tumshuq is an ancient city in the Tarim Basin region of Xinjiang, China, historically associated with the Saka (Scythian) peoples and their Eastern Iranian languages.
  • D. Tanto
    Tanto was a former town in Hyōgo Prefecture, Japan, that later became part of the expanded city of Toyooka through municipal merger.
  • E. Tyto
    Tyto is a genus of medium-sized owls best known for including the widespread barn owl and its close relatives.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Tudó
Triple: [Pepita Tudó, familyName, Tudó]
Generated description
Tudó is the surname of Pepita Tudó, a Spanish woman historically known as the mistress of Manuel de Godoy, a powerful statesman in late 18th- and early 19th-century Spain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tudó
Target entity description: Tudó is the surname of Pepita Tudó, a Spanish woman historically known as the mistress of Manuel de Godoy, a powerful statesman in late 18th- and early 19th-century Spain.
  • A. Tuder
    Tuder was an important ancient Umbrian settlement in central Italy, known today as the hilltop town of Todi.
  • B. Taznatit
    Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
  • C. Tumshuq
    Tumshuq is an ancient city in the Tarim Basin region of Xinjiang, China, historically associated with the Saka (Scythian) peoples and their Eastern Iranian languages.
  • D. Tanto
    Tanto was a former town in Hyōgo Prefecture, Japan, that later became part of the expanded city of Toyooka through municipal merger.
  • E. Tyto
    Tyto is a genus of medium-sized owls best known for including the widespread barn owl and its close relatives.
  • F. None of above. chosen

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_69d6ab6856488190b5d31178d5015f8e completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cdc42988190b4e2a6591a6f919d completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60ac3ce008190856a917c2c75862a completed May 2, 2026, 2:31 p.m.
NEDg Description generation batch_69f60f220554819088c0aa5706f44856 completed May 2, 2026, 2:50 p.m.
NED2 Entity disambiguation (via description) batch_69f60f9f40f48190b60be483d1922b22 completed May 2, 2026, 2:52 p.m.
Created at: April 8, 2026, 9:52 p.m.