Triple
T3994130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walton H. Walker |
E87059
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Johnny Walker
Johnny Walker was the nickname of U.S. Army General Walton H. Walker, a prominent World War II and Korean War commander.
|
E404262
|
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: Johnny Walker | Statement: [Walton H. Walker, nickname, Johnny Walker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johnny Walker Context triple: [Walton H. Walker, nickname, Johnny Walker]
-
A.
William Grant Sherry
William Grant Sherry was an American artist and World War II veteran best known as the third husband of actress Bette Davis.
-
B.
Hennessy
Hennessy is a surname most prominently associated with John L. Hennessy, a renowned computer scientist and former president of Stanford University.
-
C.
Hennessy
Hennessy is a world-renowned French cognac producer, recognized as one of the leading and most prestigious brands in the global spirits industry.
-
D.
Ballantine
Ballantine is the surname of the individual after whom the prestigious Stuart Ballantine Medal for scientific and engineering achievement is named.
-
E.
Will Carling
Will Carling is a former England rugby union captain and centre who led the national team through a highly successful period in the late 1980s and early 1990s.
- 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: Johnny Walker Triple: [Walton H. Walker, nickname, Johnny Walker]
Generated description
Johnny Walker was the nickname of U.S. Army General Walton H. Walker, a prominent World War II and Korean War commander.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Johnny Walker Target entity description: Johnny Walker was the nickname of U.S. Army General Walton H. Walker, a prominent World War II and Korean War commander.
-
A.
William Grant Sherry
William Grant Sherry was an American artist and World War II veteran best known as the third husband of actress Bette Davis.
-
B.
Hennessy
Hennessy is a surname most prominently associated with John L. Hennessy, a renowned computer scientist and former president of Stanford University.
-
C.
Hennessy
Hennessy is a world-renowned French cognac producer, recognized as one of the leading and most prestigious brands in the global spirits industry.
-
D.
Ballantine
Ballantine is the surname of the individual after whom the prestigious Stuart Ballantine Medal for scientific and engineering achievement is named.
-
E.
Will Carling
Will Carling is a former England rugby union captain and centre who led the national team through a highly successful period in the late 1980s and early 1990s.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa1d9d8c8190982d092a73d38564 |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5403970e08190bb491048b1bd7b16 |
completed | March 14, 2026, 11:02 a.m. |
| NEDg | Description generation | batch_69b54112e3788190800e295a745c4689 |
completed | March 14, 2026, 11:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b541808d548190987ad1538c647664 |
completed | March 14, 2026, 11:07 a.m. |
Created at: March 9, 2026, 3:33 p.m.