Triple
T4660266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Male Artist of the Year |
E102511
|
entity |
| Predicate | sexOrGenderOfRecipients |
P72
|
FINISHED |
| Object | male |
—
|
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: male | Statement: [New Male Artist of the Year, sexOrGenderOfRecipients, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sexOrGenderOfRecipients Context triple: [New Male Artist of the Year, sexOrGenderOfRecipients, male]
-
A.
hasGenderOfRecipients
Indicates the gender category or composition of the recipients involved in a given relationship or action.
-
B.
sexOrGender
chosen
Indicates that one entity has a specified biological sex or socially constructed gender identity.
-
C.
sexType
Indicates the specific category or type of sexual activity or sexual relationship involved between entities.
-
D.
sexStatus
Indicates whether and how a sexual relationship or sexual activity exists or has occurred between the related entities.
-
E.
hasFemaleRecipients
Indicates that the subject entity has one or more recipients who are female.
- 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_69bd43d823288190952279faa0d1d066 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6328387c81909a500e694a739e6e |
completed | March 20, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69bd62126b0c81909ba3f21b21e30d54 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:15 p.m.