Triple
T18482409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Girl |
E451592
|
entity |
| Predicate | featuresClubSetting |
P32516
|
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: [Bad Girl, featuresClubSetting, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresClubSetting Context triple: [Bad Girl, featuresClubSetting, yes]
-
A.
featuresClubs
Indicates that something includes or presents one or more clubs as part of its composition, content, or offering.
-
B.
featuresSetting
chosen
Indicates that something includes, presents, or highlights a particular setting as a notable or primary aspect.
-
C.
countryClubSetting
Indicates a setting or context that takes place within or is characteristic of a country club environment.
-
D.
featuresNISAClubs
Indicates that something includes or presents NISA clubs as part of its content, composition, or participants.
-
E.
supportedClub
Indicates that one entity has given their backing, endorsement, or assistance to a particular club.
- 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e531d49a1881908cc2ad6132953c96 |
completed | April 19, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69e469d671088190b619de96ea6f92ab |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:35 a.m.