Triple
T14778113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Most Girls |
E347315
|
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: [Most Girls, writer, Oscar Holter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oscar Holter Context triple: [Most Girls, 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.
Ole Hansen
Ole Hansen is a Norwegian politician who served as Minister of Defence and was a prominent figure in early 20th-century Norwegian public life.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec817c39081909b08a0ffdfce9936 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dbced588190ab7712c7ad50ee67 |
completed | May 9, 2026, 2:36 a.m. |
Created at: April 10, 2026, 1:31 a.m.