Triple
T8764230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Ocean |
E208288
|
entity |
| Predicate | publiclyDiscussedSexualityIn |
P48177
|
FINISHED |
| Object | 2012 open letter |
—
|
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: 2012 open letter | Statement: [Frank Ocean, publiclyDiscussedSexualityIn, 2012 open letter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publiclyDiscussedSexualityIn Context triple: [Frank Ocean, publiclyDiscussedSexualityIn, 2012 open letter]
-
A.
hasSexualityCharacteristic
Indicates that an entity possesses a specific sexual orientation or sexuality-related characteristic.
-
B.
sexualOrientationRevealedIn
chosen
Indicates that an entity’s sexual orientation is disclosed, made known, or becomes apparent within a specified context, medium, or situation.
-
C.
coneSex
Indicates a sexual or mating relationship involving a cone-shaped structure or entity.
-
D.
standardSex
Indicates that two entities share the same biological sex or gender classification.
-
E.
depictsSex
Indicates that one entity visually represents or portrays sexual activity or sexual content involving another entity.
- 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5dfdef9881908a7f079d87e8e338 |
completed | March 31, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1884bc8190a46e8308db31f7ab |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:40 p.m.