Triple
T36265446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Room (2015 film) |
E892207
|
entity |
| Predicate | oscarAwardRecipient |
P10689
|
FINISHED |
| Object | Brie Larson |
—
|
NE NERFINISHED |
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: Brie Larson | Statement: [Room (2015 film), oscarAwardRecipient, Brie Larson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oscarAwardRecipient Context triple: [Room (2015 film), oscarAwardRecipient, Brie Larson]
-
A.
supportingActorAwardRecipient
Indicates that an entity has received an award specifically for a supporting acting role in a performance or production.
-
B.
oscarCategoryWon
Indicates that an entity has won an Academy Award in the specified Oscar category.
-
C.
oscarAward
chosen
Indicates that an entity has received or been honored with an Academy Award (Oscar).
-
D.
oscarRecord
Indicates that an entity has a record or entry associated with the Oscars, such as a nomination, win, or related recognition.
-
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_69f76e4699188190af045b11a840ce31 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b6267e488190bbebcd8b4acc7e1b |
completed | May 3, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c44390819084fb5558b354658f |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:09 p.m.