Triple

T11734250
Position Surface form Disambiguated ID Type / Status
Subject Battle of Oliwa E278984 entity
Predicate shipInvolved P862 FINISHED
Object Solen
Solen was a notable warship that took part in the early 17th-century naval conflicts between Sweden and the Polish–Lithuanian Commonwealth.
 E942336 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: Solen | Statement: [Battle of Oliwa, shipInvolved, Solen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Solen
Context triple: [Battle of Oliwa, shipInvolved, Solen]
  • A. Sulden
    Sulden is a small alpine village and ski resort in South Tyrol, northern Italy, known for its dramatic high-mountain scenery in the Ortler Alps.
  • B. Gravina
    Gravina is an Italian surname historically associated with notable figures in politics, the military, and the arts.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Moura
    Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
  • E. Moura
    Moura is a Portuguese-language surname commonly found in Brazil and other Lusophone countries, associated with various notable figures in arts, sports, and public life.
  • 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: Solen
Triple: [Battle of Oliwa, shipInvolved, Solen]
Generated description
Solen was a notable warship that took part in the early 17th-century naval conflicts between Sweden and the Polish–Lithuanian Commonwealth.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Solen
Target entity description: Solen was a notable warship that took part in the early 17th-century naval conflicts between Sweden and the Polish–Lithuanian Commonwealth.
  • A. Sulden
    Sulden is a small alpine village and ski resort in South Tyrol, northern Italy, known for its dramatic high-mountain scenery in the Ortler Alps.
  • B. Gravina
    Gravina is an Italian surname historically associated with notable figures in politics, the military, and the arts.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Moura
    Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
  • E. Moura
    Moura is a Portuguese-language surname commonly found in Brazil and other Lusophone countries, associated with various notable figures in arts, sports, and public life.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4daa7f48190896fc7653e9dd70b completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef8406fe8881909722ecb040087e68 completed April 27, 2026, 3:43 p.m.
NEDg Description generation batch_69ef9b68309081909f3f614efeeb2ab1 completed April 27, 2026, 5:22 p.m.
NED2 Entity disambiguation (via description) batch_69efd6aba82c81909ff22e6b26db3cfe completed April 27, 2026, 9:35 p.m.
Created at: April 8, 2026, 9:41 p.m.