Triple
T7818182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickey Spillane |
E181063
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Frank
Frank is the given first name of American crime novelist Mickey Spillane, best known for creating the hard-boiled detective Mike Hammer.
|
E694944
|
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 | Statement: [Mickey Spillane, givenName, Frank]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Context triple: [Mickey Spillane, givenName, Frank]
-
A.
Frank
Frank is the given name of the American painter, sculptor, and printmaker Frank Stella, a leading figure in minimalism and post-painterly abstraction.
-
B.
Frank
Frank is the given name of the renowned Canadian-American architect Frank Gehry, celebrated for his deconstructivist and sculptural building designs.
-
C.
Frank
Frank is a key supporting character in the post-apocalyptic horror film "28 Days Later," known as a protective father trying to keep his daughter safe amid a devastating viral outbreak in London.
-
D.
Frank
Frank is the given name of Frank Abagnale Jr., the infamous former con artist whose life inspired the film "Catch Me If You Can."
-
E.
Frank
Frank is the given name of British screenwriter and children's author Frank Cottrell-Boyce.
- 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 Triple: [Mickey Spillane, givenName, Frank]
Generated description
Frank is the given first name of American crime novelist Mickey Spillane, best known for creating the hard-boiled detective Mike Hammer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Frank Target entity description: Frank is the given first name of American crime novelist Mickey Spillane, best known for creating the hard-boiled detective Mike Hammer.
-
A.
Frank
Frank is the nickname of Frank Sheeran, an American labor union official and alleged mob hitman whose life inspired the film "The Irishman."
-
B.
Frank
Frank is the given name of filmmaker Frank Darabont, the acclaimed director and screenwriter known for works such as The Shawshank Redemption and The Green Mile.
-
C.
Frank
Frank is the given name of Frank McCourt, the Irish-American teacher and Pulitzer Prize–winning author best known for his memoir "Angela’s Ashes."
-
D.
Frank
Frank is the given name of pioneering science fiction illustrator Frank R. Paul, known for his influential early magazine and pulp cover art.
-
E.
Frank
Frank is the given name of Frank Oz, the renowned puppeteer, actor, and director best known for his work with the Muppets and on Star Wars.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf9708bdc8190a5154efe0f96f458 |
completed | March 30, 2026, 10:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb149266e88190a582b11d68702a6a |
completed | March 31, 2026, 12:25 a.m. |
| NEDg | Description generation | batch_69cb1732bb608190aa776f23f0dc6189 |
completed | March 31, 2026, 12:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb1a62569c81908709d814954f667e |
completed | March 31, 2026, 12:50 a.m. |
Created at: March 30, 2026, 4:40 p.m.