Triple

T23233572
Position Surface form Disambiguated ID Type / Status
Subject Duke of Suárez E581225 entity
Predicate titleHolder P1911 FINISHED
Object Adolfo Suárez Illana
Adolfo Suárez Illana is a Spanish lawyer, businessman, and politician, known as the son of Spain’s first democratic Prime Minister after Franco, Adolfo Suárez González.
E140784 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: Adolfo Suárez Illana | Statement: [Duke of Suárez, titleHolder, Adolfo Suárez Illana]
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: Adolfo Suárez Illana
Triple: [Duke of Suárez, titleHolder, Adolfo Suárez Illana]
Generated description
Adolfo Suárez Illana is a Spanish lawyer, businessman, and politician, known as the son of Spain’s first democratic Prime Minister after Franco, Adolfo Suárez González.

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_69e2460556f88190be1744a84a84173f completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f192e70b2c8190abede6e3cd9344f7 completed April 29, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f75e5abc48190ab4fc496446a6f26 completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f77372e188190bbf5c1a77de0833c completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77d47ea08190828e5f5f9f0e3899 completed May 21, 2026, 9:23 p.m.
Created at: April 17, 2026, 4:09 p.m.