Triple

T19539582
Position Surface form Disambiguated ID Type / Status
Subject Carlos Baerga E488859 entity
Predicate familyName P18 FINISHED
Object Baerga
Baerga is a Spanish-origin surname most notably associated with former Major League Baseball All-Star second baseman Carlos Baerga.
 E1387430 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: Baerga | Statement: [Carlos Baerga, familyName, Baerga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Baerga
Context triple: [Carlos Baerga, familyName, Baerga]
  • A. Cullera
    Cullera is a coastal town in eastern Spain known for its Mediterranean beaches, historic castle, and location at the mouth of the Júcar River.
  • B. Sarria
    Sarria is a historic town in the province of Lugo, Galicia, Spain, known today as a major starting point on the Camino de Santiago pilgrimage route.
  • C. La Bañeza
    La Bañeza is a small historic city in northwestern Spain known for its cultural festivals and traditional architecture.
  • D. Burriana
    Burriana is a coastal town in Spain’s Valencian Community known for its Mediterranean beaches and role as a holiday resort on the Costa del Azahar.
  • E. Bagergue
    Bagergue is a small picturesque village in the Val d'Aran region of Catalonia, Spain, known for its traditional stone architecture and mountain scenery.
  • 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: Baerga
Triple: [Carlos Baerga, familyName, Baerga]
Generated description
Baerga is a Spanish-origin surname most notably associated with former Major League Baseball All-Star second baseman Carlos Baerga.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Baerga
Target entity description: Baerga is a Spanish-origin surname most notably associated with former Major League Baseball All-Star second baseman Carlos Baerga.
  • A. Cullera
    Cullera is a coastal town in eastern Spain known for its Mediterranean beaches, historic castle, and location at the mouth of the Júcar River.
  • B. Sarria
    Sarria is a historic town in the province of Lugo, Galicia, Spain, known today as a major starting point on the Camino de Santiago pilgrimage route.
  • C. La Bañeza
    La Bañeza is a small historic city in northwestern Spain known for its cultural festivals and traditional architecture.
  • D. Burriana
    Burriana is a coastal town in Spain’s Valencian Community known for its Mediterranean beaches and role as a holiday resort on the Costa del Azahar.
  • E. Bagergue
    Bagergue is a small picturesque village in the Val d'Aran region of Catalonia, Spain, known for its traditional stone architecture and mountain scenery.
  • 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63871d00881909ed7371ae5577957 completed April 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a077ed4f3148190aee5530e31447d4e completed May 15, 2026, 8:15 p.m.
NEDg Description generation batch_6a077f74e4fc81909fd1c65af64ba68f completed May 15, 2026, 8:17 p.m.
NED2 Entity disambiguation (via description) batch_6a0780e305f08190805e21212dec0b39 completed May 15, 2026, 8:24 p.m.
Created at: April 10, 2026, 1:41 p.m.