Triple
T12479022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Adventures of Kathlyn |
E298253
|
entity |
| Predicate | starred |
P5563
|
FINISHED |
| Object |
Tom Santschi
Tom Santschi was an American silent film actor best known for his rugged roles in early Westerns and adventure serials.
|
E987133
|
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: Tom Santschi | Statement: [The Adventures of Kathlyn, starred, Tom Santschi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Santschi Context triple: [The Adventures of Kathlyn, starred, Tom Santschi]
-
A.
Tom Schaul
Tom Schaul is a machine learning researcher known for his contributions to deep reinforcement learning, including co-developing the Dueling DQN architecture.
-
B.
Frank Teschemacher
Frank Teschemacher was an influential early Chicago jazz clarinetist and saxophonist known for his role in shaping the Chicago style of the 1920s and early 1930s.
-
C.
Paul Palmentola
Paul Palmentola was a mid-20th-century American art director known for his work on historical and adventure films.
-
D.
Tino Gross
Tino Gross is a musician best known as a member of Kid Rock’s backing band, Twisted Brown Trucker.
-
E.
Peter Barsocchini
Peter Barsocchini is an American screenwriter and producer best known for writing and creating Disney Channel’s hugely popular "High School Musical" franchise.
- 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: Tom Santschi Triple: [The Adventures of Kathlyn, starred, Tom Santschi]
Generated description
Tom Santschi was an American silent film actor best known for his rugged roles in early Westerns and adventure serials.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tom Santschi Target entity description: Tom Santschi was an American silent film actor best known for his rugged roles in early Westerns and adventure serials.
-
A.
Tom Schaul
Tom Schaul is a machine learning researcher known for his contributions to deep reinforcement learning, including co-developing the Dueling DQN architecture.
-
B.
Frank Teschemacher
Frank Teschemacher was an influential early Chicago jazz clarinetist and saxophonist known for his role in shaping the Chicago style of the 1920s and early 1930s.
-
C.
Paul Palmentola
Paul Palmentola was a mid-20th-century American art director known for his work on historical and adventure films.
-
D.
Tino Gross
Tino Gross is a musician best known as a member of Kid Rock’s backing band, Twisted Brown Trucker.
-
E.
Peter Barsocchini
Peter Barsocchini is an American screenwriter and producer best known for writing and creating Disney Channel’s hugely popular "High School Musical" franchise.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dcdcd3c81908ad29145db241408 |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64ba5efc881909784037b95f7bbe3 |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64ce0ca288190bbbcb5459f914c19 |
completed | May 2, 2026, 7:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64df6488481909dea8387e7000d15 |
completed | May 2, 2026, 7:18 p.m. |
Created at: April 8, 2026, 9:56 p.m.