Triple
T17747180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Save Me |
E443017
|
entity |
| Predicate | artist |
P184
|
FINISHED |
| Object | Remy Zero |
—
|
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: Remy Zero | Statement: [Save Me, artist, Remy Zero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Remy Zero Context triple: [Save Me, artist, Remy Zero]
-
A.
Remy Zero
chosen
Remy Zero is an American alternative rock band best known for their song "Save Me," which gained widespread recognition as the opening theme for the television series Smallville.
-
B.
J-Remy
J-Remy is a writer known for contributions to the works associated with the band Down.
-
C.
Remy
Remy is the ambitious, food-loving rat and main protagonist of Pixar’s animated film "Ratatouille," known for his exceptional culinary talent and dream of becoming a chef in Paris.
-
D.
Remy
Remy is a fictional character portrayed as a family member of Brian Dennehy’s character Django.
-
E.
Remm
Remm is a Japanese hotel brand known for its compact, design-focused “sleep-centric” business hotels operated by Hankyu Hanshin Hotels.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47ad33160819093c9bbd3c8957314 |
completed | April 19, 2026, 6:48 a.m. |
Created at: April 10, 2026, 10:10 a.m.