Triple

T19536763
Position Surface form Disambiguated ID Type / Status
Subject Lady Rose Gilman E488786 entity
Predicate middleName P143 FINISHED
Object Victoria
Victoria is the middle name of Lady Rose Gilman, a member of the British royal family.
E1382105 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: [Lady Rose Gilman, middleName, Victoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria
Context triple: [Lady Rose Gilman, middleName, 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 coastal city on the southern tip of Vancouver Island known for its historic architecture, mild climate, and vibrant tourism industry.
  • C. Victoria
    Victoria is a vengeful vampire antagonist from the Twilight series who relentlessly hunts Bella Swan and opposes the Cullen family.
  • D. 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.
  • 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. 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: [Lady Rose Gilman, middleName, Victoria]
Generated description
Victoria is the middle name of Lady Rose Gilman, a member of the British royal family.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Victoria
Target entity description: Victoria is the middle name of Lady Rose Gilman, a member of the British royal family.
  • A. Victoria
    Victoria was the long-reigning 19th-century British queen whose era saw vast industrial, cultural, and imperial expansion.
  • B. 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."
  • 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 is the full given name of the fictional soap opera character Viki Lord from the American television series "One Life to Live."
  • 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. 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_69e6386f0fac819081bbc29172c8965e completed April 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a074e6af03481909b135b47eb3b1d4b completed May 15, 2026, 4:48 p.m.
NEDg Description generation batch_6a074f9e45308190928cd2e018524985 completed May 15, 2026, 4:53 p.m.
NED2 Entity disambiguation (via description) batch_6a075066d5b48190843297c868e4d6df completed May 15, 2026, 4:57 p.m.
Created at: April 10, 2026, 1:41 p.m.