Triple
T13486581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Lot Like Love |
E318518
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Kal Penn |
E582612
|
NE FINISHED |
How this triple was built (2 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: Kal Penn | Statement: [A Lot Like Love, castMember, Kal Penn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kal Penn Context triple: [A Lot Like Love, castMember, Kal Penn]
-
A.
Kal Penn
chosen
Kal Penn is an American actor and former White House staff member best known for his roles in the "Harold & Kumar" film series and the TV show "House."
-
B.
Greg Sanders
Greg Sanders is a quirky, music-loving forensic scientist who evolves from a DNA lab technician to a field investigator on the TV series CSI: Crime Scene Investigation.
-
C.
Ben Schwartz
Ben Schwartz is an American actor, comedian, and voice performer known for roles in projects like Parks and Recreation and for voicing animated characters in films and television.
-
D.
Seth Gabel
Seth Gabel is an American actor known for his roles in television series such as "Fringe," "Salem," and "Nip/Tuck."
-
E.
Adam Pally
Adam Pally is an American actor and comedian best known for his roles on the TV series "Happy Endings" and "The Mindy Project."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf3a15b48190b63fb59e926a97ae |
completed | April 12, 2026, 2:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d8c942481909858e340944ed57c |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:42 p.m.