Triple
T11088646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rose Byrne |
E262189
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mary
Mary is the birth name of Australian actress Rose Byrne, known for her roles in films like "Bridesmaids" and the "X-Men" series.
|
E904110
|
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: Mary | Statement: [Rose Byrne, givenName, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Rose Byrne, givenName, Mary]
-
A.
Mary
Mary, Princess Royal and Countess of Harewood, was a daughter of King George V and Queen Mary of the United Kingdom and a prominent British royal figure in the early to mid-20th century.
-
B.
Mary
Mary is a fictional character in B.F. Skinner’s utopian novel "Walden Two," representing one of the community’s young members shaped by its behaviorist social principles.
-
C.
Mary
Mary is the middle name of Katherine Mary Dewar, a component of her full personal name.
-
D.
Mary
Mary is the given name of Mary J. Blige, the acclaimed American singer, songwriter, and actress often called the "Queen of Hip-Hop Soul."
-
E.
Mary
Mary is the given name of Mary Catherine Bateson, an American cultural anthropologist and writer known for her work on learning and the human life cycle.
- 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: Mary Triple: [Rose Byrne, givenName, Mary]
Generated description
Mary is the birth name of Australian actress Rose Byrne, known for her roles in films like "Bridesmaids" and the "X-Men" series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Target entity description: Mary is the birth name of Australian actress Rose Byrne, known for her roles in films like "Bridesmaids" and the "X-Men" series.
-
A.
Mary
Mary is the birth name of the acclaimed British actress Vivien Leigh, renowned for her roles in "Gone with the Wind" and "A Streetcar Named Desire."
-
B.
Mary
Mary is the given name of American character actress Marjorie Main, known for her roles in classic Hollywood films.
-
C.
Mary
Mary is the given name of American silent film actress Mae Marsh, known for her roles in early 20th-century cinema.
-
D.
Mary
Mary is the given name of May Robson, an English-born Australian-American stage and film actress known for her character roles in early Hollywood cinema.
-
E.
Mary
Mary is the given name of American actress, singer, director, and screenwriter Mary Kay Place, known for her work in film and television since the 1970s.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799e844b08190987c7c8e8d626510 |
completed | April 9, 2026, 12:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e7b68ca88190a26ee54eb873c9cf |
completed | April 18, 2026, 8:21 p.m. |
| NEDg | Description generation | batch_69e3f2cafc008190a3504999297f1e4e |
completed | April 18, 2026, 9:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3f488819081908f9a4225279cde6b |
completed | April 18, 2026, 9:15 p.m. |
Created at: April 8, 2026, 9:27 p.m.