Triple
T18139982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samba |
E434234
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Ludovico Einaudi |
—
|
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: Ludovico Einaudi | Statement: [Samba, musicBy, Ludovico Einaudi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ludovico Einaudi Context triple: [Samba, musicBy, Ludovico Einaudi]
-
A.
Ludovico Einaudi
chosen
Ludovico Einaudi is an Italian pianist and composer renowned for his minimalist, emotionally evocative contemporary classical music widely used in film and television.
-
B.
Yann Tiersen
Yann Tiersen is a French musician and composer best known internationally for his whimsical, minimalist score to the film "Amélie."
-
C.
Mario Einaudi
Mario Einaudi was an Italian-born political scientist and academic who became a prominent scholar of comparative government in the United States.
-
D.
Nora Pärt
Nora Pärt is the wife and close collaborator of Estonian composer Arvo Pärt, known for supporting and helping manage his artistic career.
-
E.
Arvo Pärt
Arvo Pärt is an Estonian composer renowned for his spiritually inspired minimalist style, particularly his distinctive tintinnabuli technique.
- 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de0a59d08190be74c1ecc00a8f3a |
completed | April 19, 2026, 1:52 p.m. |
Created at: April 10, 2026, 10:29 a.m.