Triple
T2644179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed Wood |
E62945
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Denise Di Novi |
E152988
|
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: Denise Di Novi | Statement: [Ed Wood, producer, Denise Di Novi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denise Di Novi Context triple: [Ed Wood, producer, Denise Di Novi]
-
A.
Denise Di Novi
chosen
Denise Di Novi is an American film producer known for her work on numerous popular films, including several Tim Burton projects and acclaimed literary adaptations.
-
B.
Donna Gigliotti
Donna Gigliotti is an Academy Award–winning American film producer known for acclaimed works such as "Shakespeare in Love" and "Silver Linings Playbook."
-
C.
Gina Ruberti
Gina Ruberti was the wife of Bruno Mussolini, the son of Italian dictator Benito Mussolini.
-
D.
Maria Scicolone
Maria Scicolone is an Italian television personality, author, and singer, also known as the younger sister of actress Sophia Loren.
-
E.
Roberta Romano
Roberta Romano is a prominent American legal scholar known for her influential work on corporate law and governance, and for serving as a long-time professor at Yale Law School.
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd90046dc81908bab3440733f1e98 |
completed | March 7, 2026, 7:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc02acc048190812d7d2d8b59058a |
completed | March 10, 2026, 6:54 a.m. |
Created at: March 6, 2026, 9:53 p.m.