Triple

T22492102
Position Surface form Disambiguated ID Type / Status
Subject Sergio Llull E556043 entity
Predicate nickname P55 FINISHED
Object Llull NE NERFINISHED

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: Llull | Statement: [Sergio Llull, nickname, Llull]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Llull
Context triple: [Sergio Llull, nickname, Llull]
  • A. Subirats
    Subirats is a municipality in Catalonia, Spain, known for its vineyards, cava production, and rural landscapes.
  • B. Altafulla
    Altafulla is a coastal town in Catalonia, Spain, known for its historic old quarter, sandy beaches, and well-preserved Roman and medieval heritage.
  • C. Baltasar
    Baltasar is a variant of the name Belshazzar, historically associated with the last king of Babylon mentioned in the biblical Book of Daniel.
  • D. Benais
    Benais is a French commune in the Indre-et-Loire department of the Loire Valley, known for its vineyards and wine production.
  • E. Ramon Llull chosen
    Ramon Llull was a 13th-century Majorcan philosopher, theologian, and writer known for his pioneering work in logic, interfaith dialogue, and the development of one of the earliest vernacular literatures in Europe.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5445bc8190b6a9481926db3355 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15caea9d081909adc90ae78999d53 completed April 29, 2026, 1:19 a.m.
Created at: April 16, 2026, 8:49 p.m.