Triple
T22587798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vicki Kennedy |
E564847
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Victoria
Victoria is the formal given name of Vicki Kennedy, an American attorney and widow of U.S. Senator Ted Kennedy.
|
E1546852
|
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: [Vicki Kennedy, givenName, Victoria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Victoria Context triple: [Vicki Kennedy, givenName, Victoria]
-
A.
Victoria
Victoria is a southeastern Australian state known for its capital city Melbourne, cultural diversity, and varied landscapes ranging from coastal regions to alpine areas.
-
B.
Victoria
Victoria is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and agricultural economy.
-
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 a British historical drama television series that chronicles the early life and reign of Queen Victoria.
-
E.
Victoria
Victoria was a German princess of Saxe-Coburg-Saalfeld best known as the mother of Queen Victoria of the United Kingdom.
- 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: [Vicki Kennedy, givenName, Victoria]
Generated description
Victoria is the formal given name of Vicki Kennedy, an American attorney and widow of U.S. Senator Ted Kennedy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Victoria Target entity description: Victoria is the formal given name of Vicki Kennedy, an American attorney and widow of U.S. Senator Ted Kennedy.
-
A.
Victoria
Victoria is the full given name of the fictional soap opera character Viki Lord from the American television series "One Life to Live."
-
B.
Victoria
Victoria is the birth name of American actress and television personality Tori Spelling, known for her role on "Beverly Hills, 90210."
-
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 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."
-
E.
Victoria
Victoria is the middle name of Lady Rose Gilman, a member of the British royal family.
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1615de7d48190b1ca46c76a1e609c |
completed | April 29, 2026, 1:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b585066a08190948ac977886f40b5 |
completed | May 18, 2026, 6:20 p.m. |
| NEDg | Description generation | batch_6a0b6f5b85548190bd54f5a13dd27c5d |
completed | May 18, 2026, 7:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b7072e43c8190ad8f8d09f61d3f7b |
completed | May 18, 2026, 8:02 p.m. |
Created at: April 17, 2026, 2:47 p.m.