Triple
T6954914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pain & Gain |
E161216
|
entity |
| Predicate | notableCharacter |
P1481
|
FINISHED |
| Object |
Daniel Lugo
Daniel Lugo is the ambitious, bodybuilding ringleader of the criminal scheme at the center of the dark comedy crime film "Pain & Gain."
|
E632452
|
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: Daniel Lugo | Statement: [Pain & Gain, notableCharacter, Daniel Lugo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Lugo Context triple: [Pain & Gain, notableCharacter, Daniel Lugo]
-
A.
Felix Rodriguez
Felix Rodriguez is a Cuban-American former CIA operative known for his involvement in covert Cold War operations, including the Bay of Pigs invasion and the capture of Che Guevara.
-
B.
Frank Dominguez
Frank Dominguez is an entrepreneur best known as a founder of the cloud-based software company Salesforce.
-
C.
Frank Dominguez
Frank Dominguez is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
-
D.
Mark Dacascos
Mark Dacascos is an American actor and martial artist known for his roles in action films and television, as well as for serving as the Chairman on the TV show "Iron Chef America."
-
E.
Matthew Saldivar
Matthew Saldivar is an American stage actor best known for his work in Broadway musicals and plays.
- 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: Daniel Lugo Triple: [Pain & Gain, notableCharacter, Daniel Lugo]
Generated description
Daniel Lugo is the ambitious, bodybuilding ringleader of the criminal scheme at the center of the dark comedy crime film "Pain & Gain."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daniel Lugo Target entity description: Daniel Lugo is the ambitious, bodybuilding ringleader of the criminal scheme at the center of the dark comedy crime film "Pain & Gain."
-
A.
Felix Rodriguez
Felix Rodriguez is a Cuban-American former CIA operative known for his involvement in covert Cold War operations, including the Bay of Pigs invasion and the capture of Che Guevara.
-
B.
Frank Dominguez
Frank Dominguez is an entrepreneur best known as a founder of the cloud-based software company Salesforce.
-
C.
Frank Dominguez
Frank Dominguez is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
-
D.
Mark Dacascos
Mark Dacascos is an American actor and martial artist known for his roles in action films and television, as well as for serving as the Chairman on the TV show "Iron Chef America."
-
E.
Matthew Saldivar
Matthew Saldivar is an American stage actor best known for his work in Broadway musicals and plays.
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dace1a94819095311e4288f01784 |
completed | March 27, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7618afb0c8190b1545328c1cee5de |
completed | March 28, 2026, 5:05 a.m. |
| NEDg | Description generation | batch_69c7623b1e5081909680e1a1811b83e0 |
completed | March 28, 2026, 5:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c762ee1a048190ada3e6fd850e468b |
completed | March 28, 2026, 5:11 a.m. |
Created at: March 27, 2026, 2:29 p.m.