Triple
T10718166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let There Be Love |
E252738
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Max Martin |
E185694
|
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: Max Martin | Statement: [Let There Be Love, producer, Max Martin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Max Martin Context triple: [Let There Be Love, producer, Max Martin]
-
A.
Max Martin
Max Martin is a Swedish songwriter and record producer renowned for crafting numerous global pop hits for artists like Britney Spears, Backstreet Boys, Taylor Swift, and Katy Perry.
-
B.
Greg Kurstin
Greg Kurstin is a Grammy-winning American producer, songwriter, and multi-instrumentalist known for his work with major artists across pop and rock music.
-
C.
RedOne
RedOne is a Moroccan-Swedish record producer and songwriter known for crafting global pop and dance hits for artists like Lady Gaga, Jennifer Lopez, and Nicki Minaj.
-
D.
Dr. Luke
Dr. Luke is an American pop music producer and songwriter known for crafting numerous chart-topping hits for major artists in the 2000s and 2010s.
-
E.
Adam Schaffer
Adam Schaffer is a fictional protagonist featured in the romantic comedy film "It's Complicated."
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6ff36558c81908682adbe7b5dce05 |
completed | April 9, 2026, 1:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbb71dd6f88190beb99ca75914fb09 |
completed | April 12, 2026, 3:15 p.m. |
Created at: April 8, 2026, 9:13 p.m.