Triple
T16047224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Jo Salter |
E389253
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mary Jo
Mary Jo is the first and middle name of American poet, editor, and academic Mary Jo Salter.
|
E1190823
|
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 Jo | Statement: [Mary Jo Salter, givenName, Mary Jo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Jo Context triple: [Mary Jo Salter, givenName, Mary Jo]
-
A.
Mary Jo
Mary Jo is the given name of Mary Jo Kopechne, the young political campaign specialist who died in the 1969 Chappaquiddick incident involving Senator Ted Kennedy.
-
B.
Mary Ruth
Mary Ruth is a fictional character featured in the American television sitcom "The Debbie Reynolds Show."
-
C.
Mary Lynn
Mary Lynn is an American actress and comedian best known for her role as computer analyst Chloe O'Brian on the television series "24."
-
D.
Mary Lou
Mary Lou is a technology innovator and entrepreneur best known for her pioneering work in display and imaging technologies, including co-founding One Laptop per Child and founding Openwater.
-
E.
Mary Lou
Mary Lou is the first American woman gymnast to win the Olympic all-around gold medal, achieved at the 1984 Los Angeles Games.
- 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 Jo Triple: [Mary Jo Salter, givenName, Mary Jo]
Generated description
Mary Jo is the first and middle name of American poet, editor, and academic Mary Jo Salter.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Jo Target entity description: Mary Jo is the first and middle name of American poet, editor, and academic Mary Jo Salter.
-
A.
Mary Jo
Mary Jo is the given name of Mary Jo Kopechne, the young political campaign specialist who died in the 1969 Chappaquiddick incident involving Senator Ted Kennedy.
-
B.
Mary Ruth
Mary Ruth is a fictional character featured in the American television sitcom "The Debbie Reynolds Show."
-
C.
Mary Lynn
Mary Lynn is an American actress and comedian best known for her role as computer analyst Chloe O'Brian on the television series "24."
-
D.
Mary Lou
Mary Lou is a technology innovator and entrepreneur best known for her pioneering work in display and imaging technologies, including co-founding One Laptop per Child and founding Openwater.
-
E.
Mary Lou
Mary Lou is the first American woman gymnast to win the Olympic all-around gold medal, achieved at the 1984 Los Angeles Games.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1835eda348190aff492f0ff668cce |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbddc25481908fca660c4f14eaff |
completed | May 10, 2026, 1:14 a.m. |
| NEDg | Description generation | batch_69ffdc915be88190a0e949fcee608242 |
completed | May 10, 2026, 1:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffdd17239c8190a3c0c4d146a279f7 |
completed | May 10, 2026, 1:19 a.m. |
Created at: April 10, 2026, 4:56 a.m.