Triple
T20408265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Sux |
E500525
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Andrew Goldstein |
—
|
NE NERFINISHED |
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: Andrew Goldstein | Statement: [Love Sux, producer, Andrew Goldstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Goldstein Context triple: [Love Sux, producer, Andrew Goldstein]
-
A.
Andrew Goldstein
chosen
Andrew Goldstein is an American songwriter and record producer known for his work with major pop and rock artists across the contemporary music industry.
-
B.
Michael Goldstein
Michael Goldstein is a relatively common personal name shared by multiple individuals across fields such as academia, business, and the arts, rather than referring to a single widely recognized public figure.
-
C.
Andrew Goldman
Andrew Goldman is a film editor known for his work on the independent feature "Tiny Furniture."
-
D.
Josh Goldstein
Josh Goldstein is a screenwriter best known for co-writing the story for Disney’s adventure film "Jungle Cruise."
-
E.
Martin Goldstein
Martin Goldstein, nicknamed "Buggsy," was an American mobster and hitman associated with Murder, Inc. during the 1930s and 1940s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a3d03ac81908f37b907ccbb5088 |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:29 a.m.