Triple
T22891087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epic (2013 film) |
E568040
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Queen Tara |
—
|
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: Queen Tara | Statement: [Epic (2013 film), mainCharacter, Queen Tara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Queen Tara Context triple: [Epic (2013 film), mainCharacter, Queen Tara]
-
A.
Queen Tara
chosen
Queen Tara is a central royal figure in the animated fantasy film "Epic," serving as the wise and noble guardian of the forest.
-
B.
Queen Ramonda
Queen Ramonda is a regal Wakandan matriarch and mother of T’Challa in Marvel’s Black Panther franchise.
-
C.
Queen Darleen
Queen Darleen is a Tanzanian singer and performer best known for her work in Bongo Flava music and her association with the influential WCB Wasafi label.
-
D.
Queen Sasha
Queen Sasha is a character from Stephen King’s fantasy novel "The Eyes of the Dragon," known as the compassionate and wise queen of Delain and mother of Prince Peter.
-
E.
Queen La
Queen La is a recurring villainess in the Tarzan stories, depicted as the powerful and often sinister queen and high priestess of the lost city of Opar.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458c23ec81908fa2570692c6614f |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f17fc59e108190a22f90c2439830fb |
completed | April 29, 2026, 3:49 a.m. |
Created at: April 17, 2026, 3:40 p.m.