Triple
T16457586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 50/50 |
E399720
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Adam Lerner
Adam Lerner is the young man diagnosed with a rare form of cancer in the dramedy film "50/50," whose journey balances humor and vulnerability as he confronts his illness.
|
E1338155
|
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: Adam Lerner | Statement: [50/50, mainCharacter, Adam Lerner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adam Lerner Context triple: [50/50, mainCharacter, Adam Lerner]
-
A.
Julian Lerner
Julian Lerner is an American child actor known for his roles in family-oriented films and television series.
-
B.
Avi Lerner
Avi Lerner is an Israeli-American film producer and founder of Millennium Films, known for financing and producing numerous action movies and franchises.
-
C.
Sy Levin
Sy Levin is a film producer best known for his work on the 1987 adaptation of "Flowers in the Attic."
-
D.
Jake Adelstein
Jake Adelstein is an American journalist and author best known for his memoir "Tokyo Vice," which chronicles his experiences reporting on crime and the yakuza for a major Japanese newspaper.
-
E.
Adam Leff
Adam Leff is an American television and film writer-producer best known for co-writing the movie "PCU" and working on various comedy projects.
- 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: Adam Lerner Triple: [50/50, mainCharacter, Adam Lerner]
Generated description
Adam Lerner is the young man diagnosed with a rare form of cancer in the dramedy film "50/50," whose journey balances humor and vulnerability as he confronts his illness.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Adam Lerner Target entity description: Adam Lerner is the young man diagnosed with a rare form of cancer in the dramedy film "50/50," whose journey balances humor and vulnerability as he confronts his illness.
-
A.
Julian Lerner
Julian Lerner is an American child actor known for his roles in family-oriented films and television series.
-
B.
Avi Lerner
Avi Lerner is an Israeli-American film producer and founder of Millennium Films, known for financing and producing numerous action movies and franchises.
-
C.
Sy Levin
Sy Levin is a film producer best known for his work on the 1987 adaptation of "Flowers in the Attic."
-
D.
Jake Adelstein
Jake Adelstein is an American journalist and author best known for his memoir "Tokyo Vice," which chronicles his experiences reporting on crime and the yakuza for a major Japanese newspaper.
-
E.
Adam Leff
Adam Leff is an American screenwriter best known for co-writing the action-comedy film "Last Action Hero."
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d7ef5cc819084cfeb1a3e39d3cc |
completed | April 18, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a052b19cde0819088bb66e41796b3dc |
completed | May 14, 2026, 1:53 a.m. |
| NEDg | Description generation | batch_6a052c02a8cc8190bba9db8bd0d3b7b5 |
completed | May 14, 2026, 1:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a052ca7b87c8190808537110bf69fb6 |
completed | May 14, 2026, 2 a.m. |
Created at: April 10, 2026, 5:10 a.m.