Triple
T977025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Women (1994 film) |
E21075
|
entity |
| Predicate | oscarNomination |
P6104
|
FINISHED |
| Object | Best Actress in a Leading Role (Winona Ryder) |
—
|
LITERAL 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: Best Actress in a Leading Role (Winona Ryder) | Statement: [Little Women (1994 film), oscarNomination, Best Actress in a Leading Role (Winona Ryder)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oscarNomination Context triple: [Little Women (1994 film), oscarNomination, Best Actress in a Leading Role (Winona Ryder)]
-
A.
oscarAward
Indicates that an entity has received or been honored with an Academy Award (Oscar).
-
B.
academyAwardNominations
chosen
Indicates that an entity has received one or more nominations for an Academy Award (Oscars).
-
C.
oscarRecord
Indicates that an entity has a record or entry associated with the Oscars, such as a nomination, win, or related recognition.
-
D.
goldenGlobeNomination
Indicates that an entity received a nomination for a Golden Globe award.
-
E.
academyAwardForBestActress
Indicates that an entity received the Academy Award for Best Actress in a leading role.
- F. None of above.
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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b46344048190b7a13b8f3ad9f455 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a8a3b08190b4538e119b13f7f5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:40 p.m.