Triple
T5198755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cash |
E117340
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Tommy Cash
Tommy Cash is an Estonian rapper and artist known for his provocative music, surreal visuals, and eccentric public persona.
|
E501480
|
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: Tommy Cash | Statement: [Cash, hasNotableBearer, Tommy Cash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tommy Cash Context triple: [Cash, hasNotableBearer, Tommy Cash]
-
A.
Tommy DeBarge
Tommy DeBarge was an American musician best known as a bassist and member of the Motown family band Switch.
-
B.
Mick Rogers
Mick Rogers is an Australian former professional road cyclist known for his time-trialling strength and multiple world championship titles in the team time trial.
-
C.
Randy Moffitt
Randy Moffitt is a former Major League Baseball relief pitcher who spent most of his career with the San Francisco Giants in the 1970s.
-
D.
Tommy Noonan
Tommy Noonan was an American film and television actor and comedian known for his character roles in 1950s Hollywood movies.
-
E.
David Gamble
David Gamble is a film editor best known for his work on the Academy Award–winning romantic comedy-drama "Shakespeare in Love."
- 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: Tommy Cash Triple: [Cash, hasNotableBearer, Tommy Cash]
Generated description
Tommy Cash is an Estonian rapper and artist known for his provocative music, surreal visuals, and eccentric public persona.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tommy Cash Target entity description: Tommy Cash is an Estonian rapper and artist known for his provocative music, surreal visuals, and eccentric public persona.
-
A.
Tommy DeBarge
Tommy DeBarge was an American musician best known as a bassist and member of the Motown family band Switch.
-
B.
Mick Rogers
Mick Rogers is an Australian former professional road cyclist known for his time-trialling strength and multiple world championship titles in the team time trial.
-
C.
Randy Moffitt
Randy Moffitt is a former Major League Baseball relief pitcher who spent most of his career with the San Francisco Giants in the 1970s.
-
D.
Tommy Noonan
Tommy Noonan was an American film and television actor and comedian known for his character roles in 1950s Hollywood movies.
-
E.
David Gamble
David Gamble is a film editor best known for his work on the Academy Award–winning romantic comedy-drama "Shakespeare in Love."
- 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_69bd4462ed04819084fcb01eb9d2fa74 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a1f154481908be5d3c9cbbef92a |
completed | March 20, 2026, 4:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bee0a115048190b7f02b5449c444d7 |
completed | March 21, 2026, 6:17 p.m. |
| NEDg | Description generation | batch_69bee67ecec08190aa3e2ae7bf1eef9b |
completed | March 21, 2026, 6:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bee6ea68888190a88f6d3208ebcfba |
completed | March 21, 2026, 6:43 p.m. |
Created at: March 20, 2026, 1:47 p.m.