Triple
T6520655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Jo Kopechne |
E148371
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mary
Mary is the first name of Mary Jo Kopechne, a political campaign specialist whose death in the 1969 Chappaquiddick incident drew national attention.
|
E148371
|
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 Jo Kopechne, givenName, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Mary Jo Kopechne, givenName, Mary]
-
A.
Mary
Mary is the given first name of the acclaimed American actress Meryl Streep.
-
B.
Mary
Mary Eleanor Darwin was a member of the Darwin family, known primarily as a descendant of the naturalist Charles Darwin.
-
C.
Mary
Mary I of England was the 16th-century Queen of England and Ireland best known for her attempt to restore Roman Catholicism and for the Marian persecutions that earned her the nickname "Bloody Mary."
-
D.
Mary
Mary is a studio album by Ghanaian rapper Sarkodie, known for its highlife influences and tribute to his late grandmother.
-
E.
Mary
Mary is the first name of American soccer legend Abby Wambach, one of the most prolific goal scorers in international women’s football.
- 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 Jo Kopechne, givenName, Mary]
Generated description
Mary is the first name of Mary Jo Kopechne, a political campaign specialist whose death in the 1969 Chappaquiddick incident drew national attention.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Target entity description: Mary is the first name of Mary Jo Kopechne, a political campaign specialist whose death in the 1969 Chappaquiddick incident drew national attention.
-
A.
Mary
chosen
Mary is the given name of Mary Jo Kopechne, the American political campaign specialist who died in the 1969 Chappaquiddick incident involving Senator Ted Kennedy.
-
B.
Mary
Mary is the given name of Mary Church Terrell, a prominent African American civil rights activist, educator, and suffragist in the late 19th and early 20th centuries.
-
C.
Mary
Mary is the first name of American soccer legend Abby Wambach, one of the most prolific goal scorers in international women’s football.
-
D.
Mary
Mary is the given name of Mary Everest Boole, a 19th-century mathematics educator known for her innovative ideas on teaching mathematics, especially to children.
-
E.
Mary
Mary is the given first name of Margaret Truman, the daughter of U.S. President Harry S. Truman and a noted author and singer.
- 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_69c687e68e748190baceb9298f32d3ed |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ad9431f081909b14b3df3414a55f |
completed | March 27, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e40c193c8190b4d7acd4530121f0 |
completed | March 27, 2026, 8:09 p.m. |
| NEDg | Description generation | batch_69c6e50db2cc8190932c4d44257acb83 |
completed | March 27, 2026, 8:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6e5eacefc819092d0e9f79d90c4a6 |
completed | March 27, 2026, 8:17 p.m. |
Created at: March 27, 2026, 1:45 p.m.