Triple
T9425391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Artist Formerly Known as Prince |
E227251
|
entity |
| Predicate | requiresDescriptionForPronunciation |
P88816
|
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: [The Artist Formerly Known as Prince, requiresDescriptionForPronunciation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requiresDescriptionForPronunciation Context triple: [The Artist Formerly Known as Prince, requiresDescriptionForPronunciation, yes]
-
A.
typeOfPronunciationDescribed
Indicates that one entity specifies or characterizes the kind or style of pronunciation associated with another entity.
-
B.
hasExampleWordPronunciation
Indicates that an entity is associated with a specific example of how a word is pronounced.
-
C.
hasPhonologicalDescription
Indicates that an entity is associated with a specific representation or description of its sound structure or phonological form.
-
D.
correctPronunciation
Indicates that one entity provides the accurate or standard way to pronounce another entity (such as a word or name).
-
E.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
- 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_69ca8436ba308190903e470776d2d893 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7c8f59dc8190854dfc0d287731c6 |
completed | April 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69cca550777c819094e1851a6127cbbc |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69cca89b3368819087a3d69270c1f185 |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:49 p.m.