Triple

T17483761
Position Surface form Disambiguated ID Type / Status
Subject Monarchy of Malta E425726 entity
Predicate monarch P403 FINISHED
Object Victoria
Victoria was the long-reigning 19th-century British queen and empress whose rule oversaw the expansion of the British Empire and the Victorian era.
E597626 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: Victoria | Statement: [Monarchy of Malta, monarch, Victoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria
Context triple: [Monarchy of Malta, monarch, Victoria]
  • A. Victoria
    Victoria is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and agricultural economy.
  • B. Victoria
    Victoria is a vengeful vampire antagonist from the Twilight series who relentlessly hunts Bella Swan and opposes the Cullen family.
  • C. Victoria
    Victoria is the birth name of American actress and model Tanya Roberts, known for her roles in "Charlie's Angels" and the James Bond film "A View to a Kill."
  • D. Victoria
    Victoria was the Spanish carrack that became the first ship to successfully circumnavigate the globe during Ferdinand Magellan’s expedition.
  • E. Victoria
    Victoria is a central London district known for its major transport hub, theatres, offices, and proximity to landmarks like Buckingham Palace.
  • 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: Victoria
Triple: [Monarchy of Malta, monarch, Victoria]
Generated description
Victoria was the long-reigning 19th-century British queen and empress whose rule oversaw the expansion of the British Empire and the Victorian era.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Victoria
Target entity description: Victoria was the long-reigning 19th-century British queen and empress whose rule oversaw the expansion of the British Empire and the Victorian era.
  • A. Victoria chosen
    Victoria was the long-reigning 19th-century British queen whose era saw vast industrial, cultural, and imperial expansion.
  • B. Victoria
    Victoria is a British historical drama television series that chronicles the early life and reign of Queen Victoria.
  • C. Victoria
    Victoria was a German princess of Saxe-Coburg-Saalfeld best known as the mother of Queen Victoria of the United Kingdom.
  • D. Victoria
    Victoria was the eldest child of Queen Victoria and Prince Albert, who became German Empress and Queen of Prussia through her marriage to Frederick III.
  • E. Victoria
    Victoria is a feminine given name of Latin origin meaning "victory," borne by numerous notable figures including queens, saints, and public personalities.
  • F. None of above.

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_69d889dccf7481909264a1844a2e9100 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451d06c2881909632845dd7a6b1e3 completed April 19, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01c935aa408190b5e611d862bda834 completed May 11, 2026, 12:19 p.m.
NEDg Description generation batch_6a01c9efa2408190992ac4ecea051f2b completed May 11, 2026, 12:22 p.m.
NED2 Entity disambiguation (via description) batch_6a01caed0ed08190b76f485cab1da514 completed May 11, 2026, 12:26 p.m.
Created at: April 10, 2026, 5:48 a.m.