Triple

T10040915
Position Surface form Disambiguated ID Type / Status
Subject Swedish Navy E205293 entity
Predicate garrison P75 FINISHED
Object Berga
Berga is a Swedish locality best known as a major naval base and training center for the Swedish Navy.
 E864861 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: Berga | Statement: [Swedish Navy, garrison, Berga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Berga
Context triple: [Swedish Navy, garrison, Berga]
  • A. Berga
    Berga is a historic town in Catalonia, Spain, known for its mountainous surroundings and the traditional Patum de Berga festival.
  • B. Besalú
    Besalú is a well-preserved medieval town in Catalonia, Spain, renowned for its Romanesque architecture and iconic 12th-century stone bridge.
  • C. Benicàssim
    Benicàssim is a coastal town in eastern Spain best known for its Mediterranean beaches and the annual Festival Internacional de Benicàssim (FIB) music festival.
  • D. Tàrrega
    Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
  • E. Palamós
    Palamós is a coastal town and popular tourist destination on Spain’s Costa Brava, known for its fishing port, beaches, and seafood cuisine.
  • 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: Berga
Triple: [Swedish Navy, garrison, Berga]
Generated description
Berga is a Swedish locality best known as a major naval base and training center for the Swedish Navy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Berga
Target entity description: Berga is a Swedish locality best known as a major naval base and training center for the Swedish Navy.
  • A. Berga
    Berga is a historic town in Catalonia, Spain, known for its mountainous surroundings and the traditional Patum de Berga festival.
  • B. Besalú
    Besalú is a well-preserved medieval town in Catalonia, Spain, renowned for its Romanesque architecture and iconic 12th-century stone bridge.
  • C. Benicàssim
    Benicàssim is a coastal town in eastern Spain best known for its Mediterranean beaches and the annual Festival Internacional de Benicàssim (FIB) music festival.
  • D. Tàrrega
    Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
  • E. Palamós
    Palamós is a coastal town and popular tourist destination on Spain’s Costa Brava, known for its fishing port, beaches, and seafood cuisine.
  • 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_69ca834f70e88190b2d74828b7767ec1 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcee2e6d881908cfa0579f9be32e4 completed April 2, 2026, 2:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69d89f0c0c588190870b2145be187908 completed April 10, 2026, 6:56 a.m.
NEDg Description generation batch_69d8a11d04fc8190a448e7c846d21cb5 completed April 10, 2026, 7:05 a.m.
NED2 Entity disambiguation (via description) batch_69d8a2b82bb48190899f37a967fef444 completed April 10, 2026, 7:11 a.m.
Created at: March 30, 2026, 8:55 p.m.