Triple
T10919786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Remi Adefarasin |
E257916
|
entity |
| Predicate | workedOn |
P3
|
FINISHED |
| Object |
Elizabeth
"Elizabeth" is a 1998 historical drama film about the early reign of Queen Elizabeth I of England, acclaimed for its performances, direction, and cinematography.
|
E64313
|
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: Elizabeth | Statement: [Remi Adefarasin, workedOn, Elizabeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Context triple: [Remi Adefarasin, workedOn, Elizabeth]
-
A.
Elizabeth
Elizabeth is the formal first name of Bess Truman, who served as First Lady of the United States as the wife of President Harry S. Truman.
-
B.
Elizabeth
Elizabeth is the middle name of Lady Sarah Chatto, a British painter and member of the extended royal family.
-
C.
Elizabeth
Elizabeth is the given name of Princess Alexandra, The Honourable Lady Ogilvy, a member of the British royal family and cousin of Queen Elizabeth II.
-
D.
Elizabeth
"Elizabeth" is a popular country and gospel song by The Statler Brothers, known for its rich harmonies and storytelling lyrics.
-
E.
Elizabeth
Elizabeth was the Duchess of York who later became Queen Elizabeth The Queen Mother, a prominent member of the British royal family in the 20th century.
- 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: Elizabeth Triple: [Remi Adefarasin, workedOn, Elizabeth]
Generated description
"Elizabeth" is a 1998 historical drama film about the early reign of Queen Elizabeth I of England, acclaimed for its performances, direction, and cinematography.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Target entity description: "Elizabeth" is a 1998 historical drama film about the early reign of Queen Elizabeth I of England, acclaimed for its performances, direction, and cinematography.
-
A.
Elizabeth
chosen
"Elizabeth" is a 1998 historical drama film that chronicles the early reign of Queen Elizabeth I of England, starring Cate Blanchett in the title role.
-
B.
Elizabeth
Elizabeth is the first name of acclaimed New Zealand filmmaker Jane Campion, known for directing films such as "The Piano."
-
C.
Elizabeth
Elizabeth is a central character in the 1960 fantasy adventure film "The 3 Worlds of Gulliver," serving as Gulliver’s devoted fiancée who accompanies him on his extraordinary voyages.
-
D.
Elizabeth
Elizabeth is the intelligent, witty, and strong-minded heroine of Jane Austen’s novel "Pride and Prejudice."
-
E.
Elizabeth
Elizabeth is a central character in the 1931 horror film "Frankenstein," serving as Henry Frankenstein’s fiancée and a key figure whose vulnerability heightens the story’s emotional and dramatic stakes.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77081a0c48190b7aa4a482032d1ea |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23bcee80481909a9ec8a03bc5266d |
completed | April 17, 2026, 1:55 p.m. |
| NEDg | Description generation | batch_69e2453f6f008190847298f4006290f7 |
completed | April 17, 2026, 2:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e288b1d64c8190b31313634b706d0a |
completed | April 17, 2026, 7:23 p.m. |
Created at: April 8, 2026, 9:22 p.m.