Triple
T21554960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walters |
E531865
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
John Walters
John Walters is a relatively common personal name shared by multiple individuals across various professions and public roles.
|
E1490457
|
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: John Walters | Statement: [Walters, hasNotableBearer, John Walters]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Walters Context triple: [Walters, hasNotableBearer, John Walters]
-
A.
Don Francis
Don Francis is an American epidemiologist and public health official known for his early work on HIV/AIDS research and prevention.
-
B.
Brian Matthews
Brian Matthews is an American actor best known for his role in the 1981 slasher film "The Burning."
-
C.
Lou Carducci
Lou Carducci is a fictional character played by American actress and model Mackenzie Foy.
-
D.
Tom Snyder
Tom Snyder was an American television personality and pioneering late-night talk show host known for his in-depth, conversational interview style on programs like "Tomorrow" and "The Late Late Show."
-
E.
Carl Kasell
Carl Kasell was a longtime NPR newscaster and beloved radio personality best known for his role as the official judge and scorekeeper on the quiz show "Wait Wait... Don't Tell Me!"
- 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: John Walters Triple: [Walters, hasNotableBearer, John Walters]
Generated description
John Walters is a relatively common personal name shared by multiple individuals across various professions and public roles.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Walters Target entity description: John Walters is a relatively common personal name shared by multiple individuals across various professions and public roles.
-
A.
Don Francis
Don Francis is an American epidemiologist and public health official known for his early work on HIV/AIDS research and prevention.
-
B.
Brian Matthews
Brian Matthews is an American actor best known for his role in the 1981 slasher film "The Burning."
-
C.
Lou Carducci
Lou Carducci is a fictional character played by American actress and model Mackenzie Foy.
-
D.
Tom Snyder
Tom Snyder was an American television personality and pioneering late-night talk show host known for his in-depth, conversational interview style on programs like "Tomorrow" and "The Late Late Show."
-
E.
Carl Kasell
Carl Kasell was a longtime NPR newscaster and beloved radio personality best known for his role as the official judge and scorekeeper on the quiz show "Wait Wait... Don't Tell Me!"
- 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_69e0c460232c81908de2c3819d17c00e |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eed2de1c248190b303a4a55b022374 |
completed | April 27, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09eee58b088190a5cfcbbe7b095bc6 |
completed | May 17, 2026, 4:37 p.m. |
| NEDg | Description generation | batch_6a09f033a55c81908d221e4b5c9c1b95 |
completed | May 17, 2026, 4:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09f0cb21a081908afa371741754eaa |
completed | May 17, 2026, 4:46 p.m. |
Created at: April 16, 2026, 6:29 p.m.