Triple
T10718164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let There Be Love |
E252738
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Oscar Holter |
E798234
|
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: Oscar Holter | Statement: [Let There Be Love, writer, Oscar Holter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oscar Holter Context triple: [Let There Be Love, writer, Oscar Holter]
-
A.
Oscar Holter
chosen
Oscar Holter is a Swedish music producer and songwriter best known for co-producing major pop hits with artists like The Weeknd.
-
B.
Oscar Lorkowski
Oscar Lorkowski is a young boy in the film "Sunshine Cleaning," serving as the son of protagonist Rose Lorkowski and a key emotional anchor in the story.
-
C.
Hans Axgil
Hans Axgil is a fictional character in the film "The Danish Girl," portrayed as a compassionate childhood friend and later love interest who supports Lili Elbe through her gender transition.
-
D.
Kurt Ludvigsen
Kurt Ludvigsen is a cinematographer best known for his work on the romantic drama film "Autumn in New York."
-
E.
Oscar Torp
Oscar Torp was a Norwegian Labour Party politician who served as Prime Minister of Norway in the early 1950s and held several other key governmental roles during his career.
- 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_69de5568489c81908a902867feffdb4f |
completed | April 14, 2026, 2:55 p.m. |
Created at: April 8, 2026, 9:13 p.m.