Triple
T9438920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Espinosa |
E227591
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Easy Money
Easy Money is a 2010 Swedish crime thriller film, based on Jens Lapidus's novel, that follows a young man's descent into Stockholm's criminal underworld.
|
E799341
|
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: Easy Money | Statement: [Daniel Espinosa, notableWork, Easy Money]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Easy Money Context triple: [Daniel Espinosa, notableWork, Easy Money]
-
A.
Easy Money
Easy Money is a 1983 comedy film starring Rodney Dangerfield as a hard-living gambler forced to change his ways to inherit a fortune.
-
B.
Easy Money
"Easy Money" is a song featured on Bruce Springsteen's 2012 rock album *Wrecking Ball*.
-
C.
easyMoney
easyMoney is a financial services brand within the easyGroup portfolio, associated with the low-cost, consumer-focused "easy" family of companies.
-
D.
Easy/Lucky/Free
"Easy/Lucky/Free" is a reflective, melancholic indie rock song by Bright Eyes that closes their 2005 album Digital Ash in a Digital Urn.
-
E.
Short Money
Short Money is a system of public funding in the United Kingdom that provides financial support to opposition parties in Parliament to help them carry out their parliamentary duties.
- 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: Easy Money Triple: [Daniel Espinosa, notableWork, Easy Money]
Generated description
Easy Money is a 2010 Swedish crime thriller film, based on Jens Lapidus's novel, that follows a young man's descent into Stockholm's criminal underworld.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Easy Money Target entity description: Easy Money is a 2010 Swedish crime thriller film, based on Jens Lapidus's novel, that follows a young man's descent into Stockholm's criminal underworld.
-
A.
Easy Money
"Easy Money" is a song featured on Bruce Springsteen's 2012 rock album *Wrecking Ball*.
-
B.
Easy Money
Easy Money is a 1983 comedy film starring Rodney Dangerfield as a hard-living gambler forced to change his ways to inherit a fortune.
-
C.
easyMoney
easyMoney is a financial services brand within the easyGroup portfolio, associated with the low-cost, consumer-focused "easy" family of companies.
-
D.
Easy/Lucky/Free
"Easy/Lucky/Free" is a reflective, melancholic indie rock song by Bright Eyes that closes their 2005 album Digital Ash in a Digital Urn.
-
E.
Short Money
Short Money is a system of public funding in the United Kingdom that provides financial support to opposition parties in Parliament to help them carry out their parliamentary duties.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee1c8c48190a2ae8673eee07e9a |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1105909248190b3e02a1aa5f06b11 |
completed | April 4, 2026, 1:21 p.m. |
| NEDg | Description generation | batch_69d111113c5c81909ff654734b211753 |
completed | April 4, 2026, 1:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d111ab40a48190bb77c1cf80ef87a8 |
completed | April 4, 2026, 1:27 p.m. |
Created at: March 30, 2026, 7:50 p.m.