Triple
T26752680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairy World Taxi Spin |
E674583
|
entity |
| Predicate | usesCharacterIP |
P35699
|
FINISHED |
| Object | The Fairly OddParents characters |
—
|
LITERAL 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: The Fairly OddParents characters | Statement: [Fairy World Taxi Spin, usesCharacterIP, The Fairly OddParents characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCharacterIP Context triple: [Fairy World Taxi Spin, usesCharacterIP, The Fairly OddParents characters]
-
A.
usesCharacter
chosen
Indicates that one entity employs, incorporates, or relies on a particular character (such as a symbol, letter, or persona) in its form, function, or representation.
-
B.
usesIP
Indicates that one entity makes use of, operates through, or is associated with a particular IP address.
-
C.
usesCharactersAs
Indicates that one entity employs or incorporates specific characters (such as letters, symbols, or glyphs) from another entity for its representation or functioning.
-
D.
usesIPFrom
Indicates that one entity operates or communicates using an IP address that originates from or is assigned to another entity.
-
E.
usesCharacterMapping
Indicates that one entity applies a defined correspondence between characters (a character mapping) to transform or interpret another entity.
- F. None of above.
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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 27, 2026, 3:54 a.m.