Triple
T13922438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Garland |
E334779
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Red
Red is the nickname of Red Garland, a renowned American jazz pianist known for his work with the Miles Davis Quintet and his influential trio recordings.
|
E1069719
|
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: Red | Statement: [Red Garland, nickname, Red]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Red Context triple: [Red Garland, nickname, Red]
-
A.
Red
Red is the famous nickname of Arnold "Red" Auerbach, the legendary Boston Celtics coach and executive known for his pivotal role in building an NBA dynasty.
-
B.
Red
Red is the nickname of William L. "Red" Whittaker, a pioneering American roboticist known for his work in field robotics and autonomous vehicles.
-
C.
Red
Red is one of the main playable heroes in the run-and-gun video game Gunstar Heroes, known for fast-paced combat and cooperative action.
-
D.
Red
Red is a small, unicycle character from Pixar’s early animated short film "Red’s Dream."
-
E.
Red
"Red" is a 2010 action-comedy film about retired black-ops agents forced back into the field, known for its ensemble cast led by Bruce Willis, Helen Mirren, Morgan Freeman, and John Malkovich.
- 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: Red Triple: [Red Garland, nickname, Red]
Generated description
Red is the nickname of Red Garland, a renowned American jazz pianist known for his work with the Miles Davis Quintet and his influential trio recordings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Red Target entity description: Red is the nickname of Red Garland, a renowned American jazz pianist known for his work with the Miles Davis Quintet and his influential trio recordings.
-
A.
Red
Red is the famous nickname of Arnold "Red" Auerbach, the legendary Boston Celtics coach and executive known for his pivotal role in building an NBA dynasty.
-
B.
Red
Red is the nickname of Red Cashion, a well-known former American football official in the National Football League.
-
C.
Red
Red is the nickname of Red Rolfe, an American Major League Baseball third baseman best known for his years with the New York Yankees in the 1930s and 1940s.
-
D.
Red
Red is the nickname of William L. "Red" Whittaker, a pioneering American roboticist known for his work in field robotics and autonomous vehicles.
-
E.
Red
"Red" is a popular song by Norwegian singer-songwriter Espen Lind, known for its melodic pop style and emotional lyrics.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2aa5c1f481908a9d8786872f08fe |
completed | April 14, 2026, 11:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce7ecb488190b96f67cad4b91968 |
completed | May 3, 2026, 10:38 p.m. |
| NEDg | Description generation | batch_69f9fd5b82f48190b0b89ddca25883cc |
completed | May 5, 2026, 2:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f9fea0a9dc8190b5b65dfec9626949 |
completed | May 5, 2026, 2:28 p.m. |
Created at: April 9, 2026, 10:16 p.m.