Triple
T23100891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cold and the Crackle |
E576021
|
entity |
| Predicate | hasContributor |
P4244
|
FINISHED |
| Object |
Phil Wales
Phil Wales is a musician known for contributing to the album "Cold and the Crackle."
|
E1569362
|
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: Phil Wales | Statement: [Cold and the Crackle, hasContributor, Phil Wales]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phil Wales Context triple: [Cold and the Crackle, hasContributor, Phil Wales]
-
A.
Jonathan Wales
Jonathan Wales is a film and television sound professional best known for his work as a re-recording mixer and sound designer on numerous high-profile projects.
-
B.
Ken Wales
Ken Wales is an American film and television producer known for his work on projects such as the historical drama series "Christy" and the biographical film "Amazing Grace."
-
C.
Richard Welsh
Richard Welsh is a film and television producer best known for his executive production work on projects such as the Hallmark Hall of Fame television film "The Magic of Ordinary Days."
-
D.
William Welsh
William Welsh was an early 20th-century American film actor known for his numerous roles in silent-era motion pictures.
-
E.
Emrys Jones
Emrys Jones was a distinguished British geographer recognized for his influential work in urban and social geography.
- 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: Phil Wales Triple: [Cold and the Crackle, hasContributor, Phil Wales]
Generated description
Phil Wales is a musician known for contributing to the album "Cold and the Crackle."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Phil Wales Target entity description: Phil Wales is a musician known for contributing to the album "Cold and the Crackle."
-
A.
Jonathan Wales
Jonathan Wales is a film and television sound professional best known for his work as a re-recording mixer and sound designer on numerous high-profile projects.
-
B.
Ken Wales
Ken Wales is an American film and television producer known for his work on projects such as the historical drama series "Christy" and the biographical film "Amazing Grace."
-
C.
Richard Welsh
Richard Welsh is a film and television producer best known for his executive production work on projects such as the Hallmark Hall of Fame television film "The Magic of Ordinary Days."
-
D.
William Welsh
William Welsh was an early 20th-century American film actor known for his numerous roles in silent-era motion pictures.
-
E.
Emrys Jones
Emrys Jones was a distinguished British geographer recognized for his influential work in urban and social geography.
- 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de8c5b4819095cddf989cade60d |
completed | April 29, 2026, 4:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c15bf72008190808e11f65736f8a5 |
completed | May 19, 2026, 7:48 a.m. |
| NEDg | Description generation | batch_6a0c167881a88190a8da82f37c47e810 |
completed | May 19, 2026, 7:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c17154a148190863ef7abe33861f0 |
completed | May 19, 2026, 7:53 a.m. |
Created at: April 17, 2026, 3:58 p.m.