Triple
T7494636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tron |
E177092
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Donald Kushner |
E241131
|
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: Donald Kushner | Statement: [Tron, producer, Donald Kushner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donald Kushner Context triple: [Tron, producer, Donald Kushner]
-
A.
Donald Kushner
chosen
Donald Kushner is an American film producer best known for producing the groundbreaking science-fiction film "Tron" (1982).
-
B.
Theodore James Kushner
Theodore James Kushner is a son of American investor and former senior White House advisor Jared Kushner and Ivanka Trump, making him a grandchild of former U.S. President Donald Trump.
-
C.
Seryl Kushner
Seryl Kushner is an American businesswoman and matriarch of the Kushner family, best known as the mother of real estate investor and former presidential advisor Jared Kushner.
-
D.
Don Katz
Don Katz is an American entrepreneur and author best known as the founder of the audiobook and spoken-word entertainment company Audible.
-
E.
Paul Wernick
Paul Wernick is an American screenwriter best known for co-writing the hit Deadpool films and other major Hollywood action-comedies.
- 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_69c69f2583808190bd1a4936c42a5815 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f57b5b4c8190ab839e6a98ee86ed |
completed | March 27, 2026, 9:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c819f00819087fef27e4f4fdc1c |
completed | March 28, 2026, 8:39 p.m. |
Created at: March 27, 2026, 3:43 p.m.