Triple
T23515192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gail Carson Levine |
E574340
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Fairest |
—
|
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: Fairest | Statement: [Gail Carson Levine, notableWork, Fairest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fairest Context triple: [Gail Carson Levine, notableWork, Fairest]
-
A.
Fairest
chosen
Fairest is a comic book spin-off of the Fables series that focuses on the stories and adventures of its female fairy-tale characters.
-
B.
Briar Rose
Briar Rose is a fairy-tale princess figure best known as the enchanted, long-sleeping heroine in adaptations of the Sleeping Beauty story.
-
C.
Queen of the Fairies
The Queen of the Fairies is a powerful and regal supernatural monarch in folklore and literature, often depicted as ruling over the fairy realm with magic and grace.
-
D.
Fairy May
Fairy May is a whimsical, childlike patient in the play "The Curious Savage," known for her fanciful stories and poignant blend of humor and vulnerability.
-
E.
The Princess
The Princess is a 2022 action-fantasy film starring Joey King as a fierce, battle-hardened royal fighting to save her kingdom.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa80d9048190ab735dddd301feb4 |
completed | April 29, 2026, 6:51 a.m. |
Created at: April 17, 2026, 6:08 p.m.