Triple
T12369914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Mapes Dodge |
E294973
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mary
Mary is a feminine given name of Hebrew origin, widely used in many cultures and historically borne by numerous notable religious and literary 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 Mapes Dodge, givenName, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Mary Mapes Dodge, givenName, Mary]
-
A.
Mary
Mary is the given name of the American suspense novelist Mary Higgins Clark, known for her bestselling mystery and thriller books.
-
B.
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.
-
C.
Mary
Mary of Lancaster was a 14th-century English noblewoman, daughter of Henry, 3rd Earl of Lancaster, and a member of the influential House of Lancaster.
-
D.
Mary
Mary is the middle name of Joseph Plunkett, the Irish nationalist, poet, and 1916 Easter Rising leader.
-
E.
Mary
Mary is the birth name of American actress, comedian, and writer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
- 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 Mapes Dodge, givenName, Mary]
Generated description
Mary is a feminine given name of Hebrew origin, widely used in many cultures and historically borne by numerous notable religious and literary 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 many cultures and historically borne by numerous notable religious and literary 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 Sidney, an English Renaissance noblewoman, writer, and literary patron.
-
C.
Mary
Mary is the given name of Mary Wollstonecraft, the pioneering 18th-century English writer and advocate of women's rights.
-
D.
Mary
Mary is the given name of Mary Tyler Peabody, an American educator and reformer known for her work in the 19th century.
-
E.
Mary
Mary is the given name of Mary McLeod Bethune, a prominent African American educator, civil rights leader, and founder of Bethune-Cookman University.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa65a608190a1597a49751185a8 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63473efd481909b2061f3b19e1aaf |
completed | May 2, 2026, 5:29 p.m. |
| NEDg | Description generation | batch_69f6356b545c819089a5f5b901afc5f2 |
completed | May 2, 2026, 5:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f636382ffc8190becfae41757a45d8 |
completed | May 2, 2026, 5:36 p.m. |
Created at: April 8, 2026, 9:54 p.m.