Triple
T1786071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara Bareilles |
E39394
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Brave |
E72797
|
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: Brave | Statement: [Sara Bareilles, notableWork, Brave]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brave Context triple: [Sara Bareilles, notableWork, Brave]
-
A.
Brave
Brave is a 2012 Pixar animated fantasy film that follows a Scottish princess, Merida, who defies tradition and inadvertently unleashes a curse she must undo to save her family.
-
B.
Brave
chosen
Brave is a privacy-focused web browser known for its built-in ad and tracker blocking, faster browsing experience, and optional cryptocurrency-based rewards system.
-
C.
Ever Onward
Ever Onward is the inspirational motto associated with the Asian Games, symbolizing continuous progress and striving for excellence in sport.
-
D.
Coco
Coco is a 2017 Pixar animated film that follows a young Mexican boy’s journey through the Land of the Dead as he uncovers his family’s history and celebrates Día de los Muertos.
-
E.
Beast
Beast is a thriller novel by Peter Benchley that centers on a deadly giant squid terrorizing a coastal community.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa650d304481908ad9bff3eadf7da6 |
completed | March 6, 2026, 5:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada9a476448190b072361fe4b41537 |
completed | March 8, 2026, 4:53 p.m. |
Created at: March 4, 2026, 7:31 p.m.