Triple
T22505967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lascia ch'io pianga |
E556388
|
entity |
| Predicate | recordedBy |
P1165
|
FINISHED |
| Object | Montserrat Caballé |
—
|
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: Montserrat Caballé | Statement: [Lascia ch'io pianga, recordedBy, Montserrat Caballé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montserrat Caballé Context triple: [Lascia ch'io pianga, recordedBy, Montserrat Caballé]
-
A.
Montserrat Caballé
chosen
Montserrat Caballé was a renowned Spanish operatic soprano celebrated for her powerful yet delicate voice and exceptional bel canto technique.
-
B.
Jordi Carreras
Jordi Carreras is a Spanish DJ and music producer known within the electronic and club music scene.
-
C.
Ana Valdés
Ana Valdés is a notable individual recognized for her contributions in her field, bearing the surname Valdés.
-
D.
Carmen Rabassa
Carmen Rabassa is known primarily as the wife of acclaimed American literary translator Gregory Rabassa.
-
E.
Ana Fabrega
Ana Fabrega is a comedian, writer, and actress known for her surreal, offbeat humor and her work on the HBO series "Los Espookys."
- 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d5bf0f0819093426d83ebd80ef0 |
completed | April 29, 2026, 1:22 a.m. |
Created at: April 16, 2026, 8:50 p.m.