Triple
T6945493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Any Love |
E160787
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Lenny Green
Lenny Green is a music producer best known for his work on the R&B album "Any Love."
|
E631892
|
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: Lenny Green | Statement: [Any Love, producer, Lenny Green]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lenny Green Context triple: [Any Love, producer, Lenny Green]
-
A.
Lenny Cole
Lenny Cole is a ruthless and manipulative London crime boss in the film "RocknRolla," known for orchestrating high-stakes real estate scams and underworld dealings.
-
B.
Dan Mason
Dan Mason is a longtime baseball executive best known for serving as the general manager of the Rochester Red Wings, a Triple-A minor league team.
-
C.
Lenny McLean
Lenny McLean was a British bare-knuckle boxer, bouncer, and actor, best known for his tough-guy persona and roles in gritty crime films.
-
D.
Jimmy Lindsey
Jimmy Lindsey is a cinematographer best known for his work on the action film "Machete."
-
E.
Son Green
Son Green is a central character in the novel "Tar Baby" by Toni Morrison, representing complex themes of identity, race, and cultural conflict.
- 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: Lenny Green Triple: [Any Love, producer, Lenny Green]
Generated description
Lenny Green is a music producer best known for his work on the R&B album "Any Love."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lenny Green Target entity description: Lenny Green is a music producer best known for his work on the R&B album "Any Love."
-
A.
Lenny Cole
Lenny Cole is a ruthless and manipulative London crime boss in the film "RocknRolla," known for orchestrating high-stakes real estate scams and underworld dealings.
-
B.
Dan Mason
Dan Mason is a longtime baseball executive best known for serving as the general manager of the Rochester Red Wings, a Triple-A minor league team.
-
C.
Lenny McLean
Lenny McLean was a British bare-knuckle boxer, bouncer, and actor, best known for his tough-guy persona and roles in gritty crime films.
-
D.
Jimmy Lindsey
Jimmy Lindsey is a cinematographer best known for his work on the action film "Machete."
-
E.
Son Green
Son Green is a central character in the novel "Tar Baby" by Toni Morrison, representing complex themes of identity, race, and cultural conflict.
- 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_69c68850419081909fb426b8f5a304c7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da8a65c48190b6862fc60f6c7f7a |
completed | March 27, 2026, 7:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7586b6f0c8190a6caad7d020e9c4d |
completed | March 28, 2026, 4:26 a.m. |
| NEDg | Description generation | batch_69c75a417b7481908846a53712ea2323 |
completed | March 28, 2026, 4:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c75abf8de881908e1ae0a46da795bc |
completed | March 28, 2026, 4:36 a.m. |
Created at: March 27, 2026, 2:28 p.m.