Triple
T14898905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penrod and Sam (1937 film) |
E359948
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Frank Fanning
Frank Fanning was an actor known for his role in the 1937 film "Penrod and Sam."
|
E1126939
|
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: Frank Fanning | Statement: [Penrod and Sam (1937 film), stars, Frank Fanning]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Fanning Context triple: [Penrod and Sam (1937 film), stars, Frank Fanning]
-
A.
William Fagan
William Fagan is a relatively obscure individual whose name is notably recorded as a bearer of the surname Fagan.
-
B.
John Fagan
John Fagan is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname Fagan.
-
C.
Andrew Fagan
Andrew Fagan is a New Zealand singer-songwriter and poet best known as the frontman of the 1980s band The Mockers and for his later solo and literary work.
-
D.
Jerry Finnerman
Jerry Finnerman was an American cinematographer best known for his visually distinctive work on the original Star Trek television series.
-
E.
Frank Hackett
Frank Hackett is a ruthless, ratings-obsessed television executive in the 1976 film "Network," emblematic of the media’s turn toward sensationalism and exploitation.
- 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: Frank Fanning Triple: [Penrod and Sam (1937 film), stars, Frank Fanning]
Generated description
Frank Fanning was an actor known for his role in the 1937 film "Penrod and Sam."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Frank Fanning Target entity description: Frank Fanning was an actor known for his role in the 1937 film "Penrod and Sam."
-
A.
William Fagan
William Fagan is a relatively obscure individual whose name is notably recorded as a bearer of the surname Fagan.
-
B.
John Fagan
John Fagan is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname Fagan.
-
C.
Andrew Fagan
Andrew Fagan is a New Zealand singer-songwriter and poet best known as the frontman of the 1980s band The Mockers and for his later solo and literary work.
-
D.
Jerry Finnerman
Jerry Finnerman was an American cinematographer best known for his visually distinctive work on the original Star Trek television series.
-
E.
Frank Hackett
Frank Hackett is a ruthless, ratings-obsessed television executive in the 1976 film "Network," emblematic of the media’s turn toward sensationalism and exploitation.
- 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_69fe72b30c6881908b80ca96fb5b716f |
completed | May 8, 2026, 11:33 p.m. |
| NEDg | Description generation | batch_69fe745da3d08190926524c9167ff45a |
completed | May 8, 2026, 11:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe75df75a88190a4ce1e1391ff07e2 |
completed | May 8, 2026, 11:46 p.m. |
Created at: April 10, 2026, 2:11 a.m.