Triple
T1215044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | You're Beautiful |
E26088
|
entity |
| Predicate | hasRadioEdit |
P25064
|
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: [You're Beautiful, hasRadioEdit, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRadioEdit Context triple: [You're Beautiful, hasRadioEdit, Yes]
-
A.
hasRadioStation
Indicates that one entity possesses, operates, or is served by a particular radio station.
-
B.
radioAdaptationDirector
Indicates that the subject served as the director of a radio adaptation of the object work or production.
-
C.
radioInterface
Indicates a relationship where one entity provides or defines the radio communication interface used by another entity for wireless connectivity or control.
-
D.
radioFormat
Indicates the specific type or style of radio programming or broadcast format associated with an entity.
-
E.
canElect
Indicates that one entity has the authority or ability to choose another entity for a position, role, or office through an election process.
- 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_69a4948331fc8190b531ac9bec71c491 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be0370b4819093618930f4eecfcc |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb62a7c08190a79dcb6ff72ac99b |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bc6d5b7881908091e40c8695ef53 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:46 p.m.