Triple
T13774090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Pirate Fairy |
E330954
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Fawn |
E1059974
|
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: Fawn | Statement: [The Pirate Fairy, featuresCharacter, Fawn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fawn Context triple: [The Pirate Fairy, featuresCharacter, Fawn]
-
A.
Fawn
Fawn is a family name most notably associated with the fictional aristocratic character Lord Fawn in Anthony Trollope’s Palliser novels.
-
B.
Fawn
chosen
Fawn is an animal-loving fairy from Disney's Tinker Bell franchise, known for her warm heart, playful spirit, and special talent for communicating with creatures.
-
C.
Faline
Faline is a young doe in Disney's animated film "Bambi," known as Bambi's childhood friend and later his mate.
-
D.
Crystal Fox
Crystal Fox is one of the official mascots of the 2002 Winter Olympics in Salt Lake City, representing local wildlife and regional culture.
-
E.
Frosine
Frosine is a clever, manipulative go-between and matchmaker in Molière’s comedy "L’Avare," known for scheming to her own advantage.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de023774b48190b19e43e87b94ba77 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b07460c081908b3836a3ec382961 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:10 p.m.