Triple
T21565221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Can Wait |
E532145
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Laura Karpman |
—
|
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: Laura Karpman | Statement: [Paris Can Wait, musicBy, Laura Karpman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Karpman Context triple: [Paris Can Wait, musicBy, Laura Karpman]
-
A.
Laura Karpman
chosen
Laura Karpman is an Emmy-winning American composer known for her innovative and genre-spanning scores for film, television, and video games.
-
B.
Anne Karpf
Anne Karpf is a British writer, sociologist, and broadcaster known for her work on family life, memory, and the social impact of media and technology.
-
C.
Linda Kramer
Linda Kramer is best known as the wife of Aerosmith drummer Joey Kramer.
-
D.
Lisa Kramer
Lisa Kramer is a supporting character in the romantic comedy film "Along Came Polly," known as one of the people in protagonist Reuben Feffer’s social and professional circle.
-
E.
Marilynn Gelfman Karp
Marilynn Gelfman Karp is an American art historian, collector, and author known for her work on material culture and everyday objects.
- 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_69e0c460db088190828c64206a450273 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eed2e777c881908de84493fa939ff3 |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 16, 2026, 6:30 p.m.