Triple

T16424113
Position Surface form Disambiguated ID Type / Status
Subject Victoria Waterfield E398893 entity
Predicate givenName P17 FINISHED
Object Victoria
Victoria is a feminine given name of Latin origin meaning "victory," widely used in many English-speaking and European countries.
E134198 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: [Victoria Waterfield, givenName, Victoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria
Context triple: [Victoria Waterfield, givenName, Victoria]
  • A. Victoria
    Victoria is a vengeful vampire antagonist from the Twilight series who relentlessly hunts Bella Swan and opposes the Cullen family.
  • B. Victoria
    Victoria was the Spanish carrack that became the first ship to successfully circumnavigate the globe during Ferdinand Magellan’s expedition.
  • C. Victoria
    Victoria is a central London district known for its major transport hub, theatres, offices, and proximity to landmarks like Buckingham Palace.
  • D. Victoria
    Victoria is a city in Chile’s Araucanía Region known for its agricultural economy and role as a local commercial and services hub.
  • E. Victoria
    Victoria is a residential neighbourhood within the town of Burgess Hill in West Sussex, England.
  • 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: [Victoria Waterfield, givenName, Victoria]
Generated description
Victoria is a feminine given name of Latin origin meaning "victory," widely used in many English-speaking and European countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Victoria
Target entity description: Victoria is a feminine given name of Latin origin meaning "victory," widely used in many English-speaking and European countries.
  • A. Victoria chosen
    Victoria is a feminine given name of Latin origin meaning "victory," borne by numerous notable figures including queens, saints, and public personalities.
  • B. Victoria
    Victoria is the Roman goddess of victory, often depicted as a winged female figure symbolizing triumph and success.
  • C. Victoria
    Victoria is the birth name of American singer-songwriter Tori Kelly, known for her powerful vocals and blend of pop, R&B, and gospel influences.
  • D. Victoria
    Victoria was the long-reigning 19th-century British queen whose era saw vast industrial, cultural, and imperial expansion.
  • E. Victoria
    Victoria is a former WWE wrestler best known for her powerful in-ring style and prominent role in the women's division during the Ruthless Aggression era.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328f9da9081908dadbdac4b2d38ec completed April 18, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c5bcc7c81909dc1d3a9a1b7f50a completed May 10, 2026, 8:05 a.m.
NEDg Description generation batch_6a003dd7e9d481908822da391112eb39 completed May 10, 2026, 8:12 a.m.
NED2 Entity disambiguation (via description) batch_6a003eb888e481908eb4ed77f86cf9f3 completed May 10, 2026, 8:15 a.m.
Created at: April 10, 2026, 5:09 a.m.