Triple
T17037443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Elizabeth Winstead |
E413357
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mary
Mary is a feminine given name of Hebrew origin, widely used in English-speaking countries and historically associated with numerous religious and cultural figures.
|
E75782
|
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: [Mary Elizabeth Winstead, givenName, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Mary Elizabeth Winstead, givenName, Mary]
-
A.
Mary
Mary is the given name of Mary Cassatt, the renowned American Impressionist painter known for her depictions of women and children.
-
B.
Mary
Mary is the middle name of Edith Tolkien, the wife of author J.R.R. Tolkien.
-
C.
Mary
Mary is the birth name of American actress, comedian, and writer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
-
D.
Mary
Mary was the wife of English churchman and historian Thomas Fuller, known for her connection to this notable 17th-century writer and clergyman.
-
E.
Mary
Mary is the given name of Dame May Whitty, a renowned English stage and film actress of the early 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: Mary Triple: [Mary Elizabeth Winstead, givenName, Mary]
Generated description
Mary is a feminine given name of Hebrew origin, widely used in English-speaking countries and historically associated with numerous religious and cultural figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Target entity description: Mary is a feminine given name of Hebrew origin, widely used in English-speaking countries and historically associated with numerous religious and cultural figures.
-
A.
Mary
chosen
Mary is a feminine given name of Hebrew origin, widely used in English-speaking and many other cultures and historically associated with numerous religious and historical figures.
-
B.
Mary
Mary is the given name of Mary Wollstonecraft, the pioneering 18th-century English writer and advocate of women's rights.
-
C.
Mary
Mary is a central figure in Christianity, venerated as the mother of Jesus and often honored as the Virgin Mary.
-
D.
Mary
Mary is the given name of Mary Sidney, an English Renaissance noblewoman, writer, and literary patron.
-
E.
Mary
Mary is the given name of Mary Tyler Peabody, an American educator and reformer known for her work in the 19th century.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f38b58819093af4054c3459726 |
completed | April 18, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b451ff88190b63f4ebddf93f153 |
completed | May 10, 2026, 11:56 p.m. |
| NEDg | Description generation | batch_6a011c84ce5481909f62e4c2a6f2a962 |
completed | May 11, 2026, 12:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a011d4b53d081909781235ded1c2b35 |
completed | May 11, 2026, 12:05 a.m. |
Created at: April 10, 2026, 5:33 a.m.