Triple
T5986586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stay Up! (Viagra) |
E133240
|
entity |
| Predicate | isHumorousSongAbout |
P43127
|
FINISHED |
| Object | erectile dysfunction |
—
|
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: erectile dysfunction | Statement: [Stay Up! (Viagra), isHumorousSongAbout, erectile dysfunction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isHumorousSongAbout Context triple: [Stay Up! (Viagra), isHumorousSongAbout, erectile dysfunction]
-
A.
isPopularSongFrom
Indicates that a song is widely liked, well-known, or frequently played and originates from a particular source, such as an artist, album, or media work.
-
B.
isLoveSong
Indicates that a song’s primary theme or content centers on romantic love or affectionate emotional relationships.
-
C.
hasHumorType
Indicates that an entity possesses or is characterized by a particular style, category, or type of humor.
-
D.
hasFictionalSong
Indicates that one entity includes, features, or is associated with a song that is fictional or exists only within a narrative context.
-
E.
hasHumorousTreatmentOf
chosen
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049de98648190962b14fd341c93da |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:04 p.m.