Triple
T14854652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trainwreck |
E349319
|
entity |
| Predicate | loveInterestCharacter |
P7325
|
FINISHED |
| Object |
Aaron Conners
Aaron Conners is the charming sports doctor who becomes the central romantic partner to Amy Schumer’s character in the comedy film "Trainwreck."
|
E1123574
|
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: Aaron Conners | Statement: [Trainwreck, loveInterestCharacter, Aaron Conners]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aaron Conners Context triple: [Trainwreck, loveInterestCharacter, Aaron Conners]
-
A.
Jason Dunham
Jason Dunham was a United States Marine and Medal of Honor recipient who sacrificed his life in Iraq by smothering a grenade to save his fellow Marines.
-
B.
Jake Ryan
Jake Ryan is an actor known for his role in Wes Anderson’s film "Asteroid City."
-
C.
Alex Convery
Alex Convery is a screenwriter best known for writing the script for the 2023 sports drama film "Air," which chronicles Nike's pursuit of Michael Jordan.
-
D.
Alex Datcher
Alex Datcher is an American actress best known for her role as a flight attendant alongside Wesley Snipes in the 1992 action film "Passenger 57."
-
E.
Adam Davenport
Adam Davenport is a bionic teenager with super strength and limited intelligence from the Disney XD series "Lab Rats."
- 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: Aaron Conners Triple: [Trainwreck, loveInterestCharacter, Aaron Conners]
Generated description
Aaron Conners is the charming sports doctor who becomes the central romantic partner to Amy Schumer’s character in the comedy film "Trainwreck."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aaron Conners Target entity description: Aaron Conners is the charming sports doctor who becomes the central romantic partner to Amy Schumer’s character in the comedy film "Trainwreck."
-
A.
Jason Dunham
Jason Dunham was a United States Marine and Medal of Honor recipient who sacrificed his life in Iraq by smothering a grenade to save his fellow Marines.
-
B.
Jake Ryan
Jake Ryan is an actor known for his role in Wes Anderson’s film "Asteroid City."
-
C.
Alex Convery
Alex Convery is a screenwriter best known for writing the script for the 2023 sports drama film "Air," which chronicles Nike's pursuit of Michael Jordan.
-
D.
Alex Datcher
Alex Datcher is an American actress best known for her role as a flight attendant alongside Wesley Snipes in the 1992 action film "Passenger 57."
-
E.
Adam Davenport
Adam Davenport is a bionic teenager with super strength and limited intelligence from the Disney XD series "Lab Rats."
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44318f0819080b6c599f2d3474f |
completed | April 14, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe65087708819084f51a043e5361e9 |
completed | May 8, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_69fe66218cb88190b8c86b359abaa14c |
completed | May 8, 2026, 10:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe66de57cc8190935d764d399f56f5 |
completed | May 8, 2026, 10:42 p.m. |
Created at: April 10, 2026, 1:54 a.m.