Triple
T10579612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tutti Frutti |
E249701
|
entity |
| Predicate | containsNonsenseSyllables |
P94749
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tutti Frutti, containsNonsenseSyllables, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsNonsenseSyllables Context triple: [Tutti Frutti, containsNonsenseSyllables, yes]
-
A.
usesSyllables
Indicates that one entity forms, expresses, or analyzes something by employing syllables as its basic units.
-
B.
hasSyllabicStructure
Indicates that an entity possesses a specific arrangement or pattern of syllables, such as their number, order, or type.
-
C.
hasSyllableStructure
Indicates that an entity (typically a word or morpheme) possesses a particular arrangement or pattern of syllables.
-
D.
hasSyllabary
Indicates that one entity possesses or is associated with a specific syllabary writing system used to represent its language or notation.
-
E.
hasSyllableCount
Indicates that one entity (typically a word or phrase) possesses a specific number of syllables given by the other entity.
- F. None of above. chosen
Provenance (4 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52757b870819085b03aa6805aa076 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51907b2b881908ab9a8594688ee06 |
completed | April 7, 2026, 2:47 p.m. |
| PDg | Predicate description generation | batch_69d5270eca0481908573b698390c5b08 |
completed | April 7, 2026, 3:47 p.m. |
Created at: April 6, 2026, 12:38 p.m.