Triple
T3357793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Tyler Moore |
E70646
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mary
Mary is the given name of American actress and television icon Mary Tyler Moore, best known for her roles in "The Dick Van Dyke Show" and "The Mary Tyler Moore Show."
|
E354283
|
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 Tyler Moore, givenName, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Mary Tyler Moore, givenName, Mary]
-
A.
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.
-
B.
Mary
Mary is the birth name of American actress, singer, and dancer Debbie Reynolds, a major Hollywood star of the mid-20th century.
-
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 a minor character in Mark Twain's novel "The Adventures of Tom Sawyer," known as Tom's kind and well-behaved cousin.
- 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 Tyler Moore, givenName, Mary]
Generated description
Mary is the given name of American actress and television icon Mary Tyler Moore, best known for her roles in "The Dick Van Dyke Show" and "The Mary Tyler Moore Show."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Target entity description: Mary is the given name of American actress and television icon Mary Tyler Moore, best known for her roles in "The Dick Van Dyke Show" and "The Mary Tyler Moore Show."
-
A.
Mary
Mary is the given first name of the acclaimed American actress Meryl Streep.
-
B.
Mary
Mary is the birth name of American actress, singer, and dancer Debbie Reynolds, a major Hollywood star of the mid-20th century.
-
C.
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."
-
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 Cassatt, the renowned American Impressionist painter known for her depictions of women and children.
- 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_69ad85a660c48190998489309a3b4869 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb244435c81908e35d2aa36ec4f46 |
completed | March 8, 2026, 5:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bbbc3a48190bc17572ba3136948 |
completed | March 12, 2026, 11:26 p.m. |
| NEDg | Description generation | batch_69b34e45a6c08190a0011eaa60f3d50a |
completed | March 12, 2026, 11:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b34eba517881908806b1ac285448ff |
completed | March 12, 2026, 11:39 p.m. |
Created at: March 8, 2026, 3:13 p.m.