Triple
T10776469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Match Point |
E254209
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Letty Aronson |
E312157
|
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: Letty Aronson | Statement: [Match Point, producer, Letty Aronson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Letty Aronson Context triple: [Match Point, producer, Letty Aronson]
-
A.
Letty Aronson
chosen
Letty Aronson is an American film producer best known for her long-running collaboration with director Woody Allen on numerous critically acclaimed movies.
-
B.
Lola Burns
Lola Burns is the glamorous yet beleaguered movie star protagonist of the 1933 screwball comedy film "Bombshell," satirizing Hollywood celebrity culture and studio manipulation.
-
C.
Letty Ortiz
Letty Ortiz is a skilled street racer, mechanic, and key member of Dominic Toretto’s crew in the Fast & Furious film franchise.
-
D.
Joan Valentine
Joan Valentine is a quick-witted, resourceful young woman who works as a journalist and adventurer in P. G. Wodehouse’s comic fiction.
-
E.
Aileen Marlowe
Aileen Marlowe was the wife of American film and television actor Hugh Marlowe.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7329d8c908190bddad40685133ea1 |
completed | April 9, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de238ff88881908676d38dca041cb4 |
completed | April 14, 2026, 11:22 a.m. |
Created at: April 8, 2026, 9:16 p.m.