Triple

T11400855
Position Surface form Disambiguated ID Type / Status
Subject Oliba Cabreta E270103 entity
Predicate givenName P17 FINISHED
Object Oliba
Oliba was a medieval Catalan count who became a prominent Benedictine abbot and one of the leading figures of the Peace and Truce of God movement.
 E923737 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: Oliba | Statement: [Oliba Cabreta, givenName, Oliba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oliba
Context triple: [Oliba Cabreta, givenName, Oliba]
  • A. Güemes
    Güemes is a Spanish surname most notably associated with Argentine independence leader Martín Miguel de Güemes.
  • B. Zuera
    Zuera is a municipality in northeastern Spain located within the autonomous community of Aragon.
  • C. Serua
    Serua is a small volcanic island in Indonesia’s Banda Sea, known for its steep terrain, active geology, and remote location within the Banda Arc.
  • D. Almansa
    Almansa is a historic town in the province of Albacete, Spain, known for its imposing medieval castle and its role as the site of a major battle in the War of the Spanish Succession.
  • E. Sugambri
    The Sugambri were an ancient Germanic tribe that lived along the lower Rhine and were known for their conflicts with the Roman Empire.
  • 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: Oliba
Triple: [Oliba Cabreta, givenName, Oliba]
Generated description
Oliba was a medieval Catalan count who became a prominent Benedictine abbot and one of the leading figures of the Peace and Truce of God movement.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oliba
Target entity description: Oliba was a medieval Catalan count who became a prominent Benedictine abbot and one of the leading figures of the Peace and Truce of God movement.
  • A. Güemes
    Güemes is a Spanish surname most notably associated with Argentine independence leader Martín Miguel de Güemes.
  • B. Zuera
    Zuera is a municipality in northeastern Spain located within the autonomous community of Aragon.
  • C. Serua
    Serua is a small volcanic island in Indonesia’s Banda Sea, known for its steep terrain, active geology, and remote location within the Banda Arc.
  • D. Almansa
    Almansa is a historic town in the province of Albacete, Spain, known for its imposing medieval castle and its role as the site of a major battle in the War of the Spanish Succession.
  • E. Sugambri
    The Sugambri were an ancient Germanic tribe that lived along the lower Rhine and were known for their conflicts with the Roman Empire.
  • 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_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d80148e2048190a716b515d78efdd1 completed April 9, 2026, 7:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58cf75ec08190a571e5178bcde274 completed April 20, 2026, 2:18 a.m.
NEDg Description generation batch_69e59777b1208190a33a50da286535ee completed April 20, 2026, 3:03 a.m.
NED2 Entity disambiguation (via description) batch_69e5a3cf9d388190944340af484b3a54 completed April 20, 2026, 3:55 a.m.
Created at: April 8, 2026, 9:34 p.m.