Triple
T2326201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Yearling (1946 film) |
E48292
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Penny Baxter
Penny Baxter is a central character in the classic American film "The Yearling," portrayed as the compassionate but practical father in a struggling post-Civil War Florida family.
|
E257114
|
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: Penny Baxter | Statement: [The Yearling (1946 film), mainCharacter, Penny Baxter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penny Baxter Context triple: [The Yearling (1946 film), mainCharacter, Penny Baxter]
-
A.
Jane Baxter
Jane Baxter was a British actress known for her work in stage and film during the mid-20th century.
-
B.
Dorys Madden
Dorys Madden is best known as the wife of Basketball Hall of Famer Julius "Dr. J" Erving.
-
C.
Frances Penney
Frances Penney was the wife of Canadian physician and humanitarian Norman Bethune, accompanying parts of his medical and political journey in the early 20th century.
-
D.
Nell Burton
Nell Burton is the daughter of filmmaker Tim Burton and actress Helena Bonham Carter.
-
E.
Nora Batty
Nora Batty is a famously stern, no-nonsense Yorkshire housewife known for her wrinkled stockings and constant scolding in the British sitcom "Last of the Summer Wine."
- 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: Penny Baxter Triple: [The Yearling (1946 film), mainCharacter, Penny Baxter]
Generated description
Penny Baxter is a central character in the classic American film "The Yearling," portrayed as the compassionate but practical father in a struggling post-Civil War Florida family.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Penny Baxter Target entity description: Penny Baxter is a central character in the classic American film "The Yearling," portrayed as the compassionate but practical father in a struggling post-Civil War Florida family.
-
A.
Jane Baxter
Jane Baxter was a British actress known for her work in stage and film during the mid-20th century.
-
B.
Dorys Madden
Dorys Madden is best known as the wife of Basketball Hall of Famer Julius "Dr. J" Erving.
-
C.
Frances Penney
Frances Penney was the wife of Canadian physician and humanitarian Norman Bethune, accompanying parts of his medical and political journey in the early 20th century.
-
D.
Nell Burton
Nell Burton is the daughter of filmmaker Tim Burton and actress Helena Bonham Carter.
-
E.
Nora Batty
Nora Batty is a famously stern, no-nonsense Yorkshire housewife known for her wrinkled stockings and constant scolding in the British sitcom "Last of the Summer Wine."
- 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc64b62a08190b5a415769ce42645 |
completed | March 7, 2026, 6:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae9615f000819092f9dc4700998b25 |
completed | March 9, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_69ae96c5a6308190b970ec78984a4e8a |
completed | March 9, 2026, 9:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae9728ebc081908e00e318bcd60e57 |
completed | March 9, 2026, 9:47 a.m. |
Created at: March 4, 2026, 7:50 p.m.