Triple
T13830590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Undun |
E332384
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object | Greg Porn |
E368248
|
NE 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: Greg Porn | Statement: [Undun, featuresArtist, Greg Porn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greg Porn Context triple: [Undun, featuresArtist, Greg Porn]
-
A.
Greg Porn
chosen
Greg Porn is an American rapper known for his collaborations with The Roots, including his featured appearance on their album "Undun."
-
B.
Jerry Brudos
Jerry Brudos was an American serial killer active in the late 1960s, known for murdering women in Oregon and for his fetishistic crimes involving women's shoes and clothing.
-
C.
Jeff Pilson
Jeff Pilson is an American bassist and producer best known for his work with the rock bands Dokken and Foreigner.
-
D.
Ron Jeremy
Ron Jeremy is an American former adult film actor who became one of the most recognizable and controversial figures in the pornography industry.
-
E.
Jeff Groth
Jeff Groth is a film editor best known for his work on the critically acclaimed 2019 psychological thriller "Joker."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0299334481908c2b271eaf06e4b7 |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8ebf2608190b1071ee6967fa8d3 |
completed | May 3, 2026, 9:06 p.m. |
Created at: April 9, 2026, 10:13 p.m.