Triple
T3239906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donkey (Shrek) |
E67941
|
entity |
| Predicate | closeFriend |
P8712
|
FINISHED |
| Object | Princess Fiona |
E341065
|
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 Fiona | Statement: [Donkey (Shrek), closeFriend, Princess Fiona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Princess Fiona Context triple: [Donkey (Shrek), closeFriend, Princess Fiona]
-
A.
Princess Fiona
Princess Fiona is a strong-willed, ogre-cursed princess from the Shrek film series who subverts traditional fairy-tale stereotypes.
-
B.
Princess Unikitty
Princess Unikitty is a hyper-energetic, part-unicorn part-cat princess from The LEGO Movie franchise known for her extreme mood swings and relentlessly cheerful personality.
-
C.
Fiona
Fiona is an American singer-songwriter and pianist known for her emotionally intense, critically acclaimed alternative music.
-
D.
Fiona
chosen
Fiona is a central character in the Shrek film series, an ogre princess known for her bravery, independence, and unconventional fairy-tale romance with Shrek.
-
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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef4c0bc819095e4f84296fe7cb6 |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28eadeff481909bd48cdf51044f86 |
completed | March 12, 2026, 10 a.m. |
Created at: March 8, 2026, 3:08 p.m.