Triple
T17065766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billie Frechette |
E414082
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mary
Mary is the given first name of Billie Frechette, the Native American woman known for her association with bank robber John Dillinger during the early 1930s.
|
E1248799
|
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: [Billie Frechette, givenName, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Billie Frechette, 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 middle name of Edith Tolkien, the wife of author J.R.R. Tolkien.
-
C.
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.
-
D.
Mary
Mary is the birth name of American actress, comedian, and writer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
-
E.
Mary
Mary is a film featuring Italian actor Marco Leonardi, known for his roles in internationally acclaimed cinema.
- 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: [Billie Frechette, givenName, Mary]
Generated description
Mary is the given first name of Billie Frechette, the Native American woman known for her association with bank robber John Dillinger during the early 1930s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Target entity description: Mary is the given first name of Billie Frechette, the Native American woman known for her association with bank robber John Dillinger during the early 1930s.
-
A.
Mary
Mary is the given first name of American actress, author, and radio host Marilu Henner.
-
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 given name of Mary Woronov, an American actress, author, and underground film icon associated with Andy Warhol’s Factory scene.
-
D.
Mary
Mary is the given name of American character actress Marjorie Main, known for her roles in classic Hollywood films.
-
E.
Mary
Mary is the given name of Mary Ludwig Hays, an American Revolutionary War figure often associated with the legendary heroine "Molly Pitcher."
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db8171348190ab68d2e4f05f7120 |
completed | April 18, 2026, 7:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01234e9a94819094618ba43b7d22b4 |
completed | May 11, 2026, 12:31 a.m. |
| NEDg | Description generation | batch_6a01245aa7ec81909fa20befa29f590c |
completed | May 11, 2026, 12:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01281c8bf08190a24d77fe6af595f4 |
completed | May 11, 2026, 12:51 a.m. |
Created at: April 10, 2026, 5:34 a.m.