Triple
T14010160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serenade (from The Student Prince) |
E337056
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Serenade |
E1036480
|
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: Serenade | Statement: [Serenade (from The Student Prince), alsoKnownAs, Serenade]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serenade Context triple: [Serenade (from The Student Prince), alsoKnownAs, Serenade]
-
A.
Serenade
chosen
"Serenade" is a popular mid-20th-century song composed by Nicholas Brodszky, known for its lush romantic melody and use in film and vocal performances.
-
B.
Serenade in Blue
"Serenade in Blue" is a popular 1942 American song, with music by Harry Warren and lyrics by Mack Gordon, that became a jazz and big band standard.
-
C.
The Serenade
The Serenade is a romantic comic opera by composer Victor Herbert that helped establish his reputation in early American musical theater.
-
D.
Serenata
Serenata is a musical composition by Portuguese composer Alfredo Keil, best known for its lyrical, romantic character within his body of work.
-
E.
Serenad
Serenad is a bestselling novel by Turkish author Zülfü Livaneli that intertwines a contemporary Istanbul narrative with a tragic love story set against the backdrop of World War II and the Holocaust.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed5cfd0819085b9c860b119a9de |
completed | April 14, 2026, 12:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbaca7bbd88190a377d3b74f3d6224 |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:19 p.m.