Triple
T7714385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Field |
E174844
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Jonathan Kaplan |
E255298
|
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: Jonathan Kaplan | Statement: [Love Field, director, Jonathan Kaplan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Kaplan Context triple: [Love Field, director, Jonathan Kaplan]
-
A.
Jonathan Kaplan
chosen
Jonathan Kaplan is an American film and television director best known for his work on the acclaimed 1988 courtroom drama "The Accused."
-
B.
Greg Kaplan
Greg Kaplan is an economist known for his research on household heterogeneity, consumption, and macroeconomic policy, and for his contributions to modern macroeconomic modeling.
-
C.
Aaron Kaplan
Aaron Kaplan is a television producer and executive known for developing and overseeing numerous network and cable series through his production company.
-
D.
Larry Kaplan
Larry Kaplan is a pioneering video game designer and programmer best known as one of the co-founders of Activision and an early developer for the Atari 2600.
-
E.
Sol Kaplan
Sol Kaplan was an American composer best known for his film and television scores, including work in mid-20th-century Hollywood.
- 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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ca8f048190a6ea27b8cee2f93e |
completed | March 27, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c98f5b43ec8190836cd5e84ece66c8 |
completed | March 29, 2026, 8:45 p.m. |
Created at: March 27, 2026, 4:04 p.m.