Triple
T7242357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank McCourt |
E156386
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
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."
|
E652272
|
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: [Frank McCourt, givenName, Frank]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Context triple: [Frank McCourt, givenName, Frank]
-
A.
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.
-
B.
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."
-
C.
Frank
Frank is the given name of British screenwriter and children's author Frank Cottrell-Boyce.
-
D.
Frank
Frank is the given name of British former professional heavyweight boxer Frank Bruno, a popular sports figure especially known in the UK.
-
E.
Frank
Frank is an alternate given name of longtime Republican U.S. Congressman Jim Sensenbrenner, who represented a Wisconsin district in the House of Representatives for four decades.
- 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: [Frank McCourt, givenName, Frank]
Generated description
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."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Frank Target entity description: 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."
-
A.
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.
-
B.
Frank
Frank is the given name of Frank Lampard, the renowned English former professional footballer and manager.
-
C.
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.
-
D.
Frank
Frank is the given name of British screenwriter and children's author Frank Cottrell-Boyce.
-
E.
Frank
Frank is the given name of Frank B. Kellogg, an American lawyer, diplomat, and Nobel Peace Prize–winning U.S. Secretary of State.
- 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_69c68827b5e481908dc05e145b2c92d4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea56756c8190996c2390902f166a |
completed | March 27, 2026, 8:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7d38efa4c8190abd6434188d8c58f |
completed | March 28, 2026, 1:11 p.m. |
| NEDg | Description generation | batch_69c7d476df7081909d6e26015ac9135f |
completed | March 28, 2026, 1:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7d551870c8190be0b37702d683fbd |
completed | March 28, 2026, 1:19 p.m. |
Created at: March 27, 2026, 2:55 p.m.