Triple
T14610350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buzz Bissinger |
E342942
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Harry
Harry is the given first name of American journalist and author Buzz Bissinger, best known for writing the nonfiction book "Friday Night Lights."
|
E1111365
|
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: Harry | Statement: [Buzz Bissinger, givenName, Harry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harry Context triple: [Buzz Bissinger, givenName, Harry]
-
A.
Harry
Harry is the given name of Harry S. Truman, the 33rd president of the United States who led the country through the end of World War II and the beginning of the Cold War.
-
B.
Harry
Harry is the given name of Harry Augustus Garfield, an American lawyer, academic, and public official who served as the first head of the U.S. Fuel Administration during World War I.
-
C.
Harry
Harry is the given name of Harry Gregson-Williams, a prominent British film composer and music producer known for his work on numerous Hollywood soundtracks.
-
D.
Harry
Harry is the given name of Lord Woolf, a prominent British judge and former Lord Chief Justice of England and Wales.
-
E.
Harry
Harry is a character in the Peaky Blinders universe who becomes a victim of Arthur Shelby’s violent control 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: Harry Triple: [Buzz Bissinger, givenName, Harry]
Generated description
Harry is the given first name of American journalist and author Buzz Bissinger, best known for writing the nonfiction book "Friday Night Lights."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harry Target entity description: Harry is the given first name of American journalist and author Buzz Bissinger, best known for writing the nonfiction book "Friday Night Lights."
-
A.
Harry
Harry is the given first name of legendary American and Canadian football coach Bud Grant, who led the Minnesota Vikings to multiple Super Bowl appearances.
-
B.
Harry
Harry is the given first name of American basketball player and coach Buddy Jeannette.
-
C.
Harry
Harry is the given name of the famed American baseball broadcaster Harry Caray, known for his exuberant announcing style and long association with the Chicago Cubs.
-
D.
Harry
Harry is the given name of Harry Kurnitz, an American playwright, screenwriter, and mystery novelist active in the mid-20th century.
-
E.
Harry
Harry is the given first name of American businessman Wayne Huizenga, known for building Fortune 500 companies in waste management, video rental, and auto sales.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb44f0dd48190a78662b5998a6722 |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda91d05e48190ac945e381d6d5dd9 |
completed | May 8, 2026, 9:13 a.m. |
| NEDg | Description generation | batch_69fdd0729b888190965a06c06b161999 |
completed | May 8, 2026, noon |
| NED2 | Entity disambiguation (via description) | batch_69fdd22967988190a1524ea3e66e58ca |
completed | May 8, 2026, 12:08 p.m. |
Created at: April 10, 2026, 1:25 a.m.