Triple
T13099986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josh Dallas |
E310692
|
entity |
| Predicate | characterRole |
P268
|
FINISHED |
| Object | Prince Charming |
E62934
|
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: Prince Charming | Statement: [Josh Dallas, characterRole, Prince Charming]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prince Charming Context triple: [Josh Dallas, characterRole, Prince Charming]
-
A.
Prince Charming
chosen
Prince Charming is the idealized fairytale prince known for rescuing and marrying Cinderella in the classic Disney story.
-
B.
Prince Hans
Prince Hans is the charming yet treacherous antagonist from Disney's Frozen, who deceitfully schemes to seize control of the kingdom of Arendelle.
-
C.
Prince Eric
Prince Eric is the brave and kind-hearted human prince who becomes Ariel’s love interest in Disney’s animated film "The Little Mermaid."
-
D.
Prince Humperdinck
Prince Humperdinck is the scheming, cowardly prince and primary antagonist in the fantasy romance film and novel "The Princess Bride."
-
E.
The Grand Duke (Disney's "Cinderella")
The Grand Duke in Disney's "Cinderella" is the King’s fussy, long-suffering advisor tasked with organizing the royal ball and later tracking down the mysterious girl who captured the Prince’s heart.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981500d34819097037b3c3c33627b |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d61bcfe88190866b4330d1669602 |
completed | May 3, 2026, 4:59 a.m. |
Created at: April 9, 2026, 9:04 p.m.