Triple
T14898908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penrod and Sam (1937 film) |
E359948
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Jack Wise
Jack Wise was an actor known for his role in the 1937 comedy film "Penrod and Sam."
|
E1125261
|
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: Jack Wise | Statement: [Penrod and Sam (1937 film), stars, Jack Wise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Wise Context triple: [Penrod and Sam (1937 film), stars, Jack Wise]
-
A.
Frank Wise
Frank Wise was an Australian politician who served as Premier of Western Australia in the 1940s and later held senior roles in public administration.
-
B.
Jerry Wisdom
Jerry Wisdom was a Bahamian sprinter known for competing in international track and field events, including the Olympic Games.
-
C.
Frank Weil
Frank Weil is an American lawyer best known as one of the founding partners of the prominent international law firm Weil, Gotshal & Manges LLP.
-
D.
Jack Wisdom
Jack Wisdom is an American planetary scientist and MIT professor known for his work on celestial mechanics and dynamical chaos in the solar system.
-
E.
Marvin Kaye
Marvin Kaye was an American editor, author, and anthologist best known for his work in fantasy, horror, and science fiction publishing.
- 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: Jack Wise Triple: [Penrod and Sam (1937 film), stars, Jack Wise]
Generated description
Jack Wise was an actor known for his role in the 1937 comedy film "Penrod and Sam."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jack Wise Target entity description: Jack Wise was an actor known for his role in the 1937 comedy film "Penrod and Sam."
-
A.
Frank Wise
Frank Wise was an Australian politician who served as Premier of Western Australia in the 1940s and later held senior roles in public administration.
-
B.
Jerry Wisdom
Jerry Wisdom was a Bahamian sprinter known for competing in international track and field events, including the Olympic Games.
-
C.
Frank Weil
Frank Weil is an American lawyer best known as one of the founding partners of the prominent international law firm Weil, Gotshal & Manges LLP.
-
D.
Jack Wisdom
Jack Wisdom is an American planetary scientist and MIT professor known for his work on celestial mechanics and dynamical chaos in the solar system.
-
E.
Marvin Kaye
Marvin Kaye was an American editor, author, and anthologist best known for his work in fantasy, horror, and science fiction publishing.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded6084574819098033a9723f3e1c4 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b6966e88190a0ed475b22a77cf1 |
completed | May 8, 2026, 11:02 p.m. |
| NEDg | Description generation | batch_69fe6d199298819081207e27dfdf485f |
completed | May 8, 2026, 11:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe6de49480819087b36c070c434bf7 |
completed | May 8, 2026, 11:12 p.m. |
Created at: April 10, 2026, 2:11 a.m.