Triple
T1629708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sleeping Beauty Castle |
E35228
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | Princess Aurora |
E68133
|
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: Princess Aurora | Statement: [Sleeping Beauty Castle, basedOn, Princess Aurora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Princess Aurora Context triple: [Sleeping Beauty Castle, basedOn, Princess Aurora]
-
A.
Sleeping Beauty
chosen
Sleeping Beauty is a classic 1959 animated fantasy film from Disney, renowned for its stylized art, iconic villain Maleficent, and the story of Princess Aurora cursed into a magical sleep.
-
B.
Rapunzel
Rapunzel is a classic fairy-tale princess best known for her extraordinarily long hair and her story of captivity in a tower and eventual escape.
-
C.
Elsa
Elsa is a feminine given name of Germanic origin, widely recognized today through its use for the main character in Disney's animated film "Frozen."
-
D.
The Evil Queen
The Evil Queen is the vain and power-hungry royal villain from Disney’s Snow White, infamous for her jealousy and use of dark magic to eliminate her rival.
-
E.
Princess Yori
Princess Yori is a fictional royal character, also known as Princess Atsuko, who appears in Japanese-inspired storytelling and media.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abb3a9b634819086b44f1574e97dcb |
completed | March 7, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad58d5acd8819090c51678ce0f63f0 |
completed | March 8, 2026, 11:09 a.m. |
Created at: March 4, 2026, 7:28 p.m.