Triple
T8675129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicolai Gedda |
E205893
|
entity |
| Predicate | numberOfRecordings |
P74853
|
FINISHED |
| Object | over 200 complete recordings and recitals |
—
|
LITERAL 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: over 200 complete recordings and recitals | Statement: [Nicolai Gedda, numberOfRecordings, over 200 complete recordings and recitals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRecordings Context triple: [Nicolai Gedda, numberOfRecordings, over 200 complete recordings and recitals]
-
A.
numberOfKnownRecordings
chosen
Indicates the total count of recordings of an entity that are currently known or documented.
-
B.
typicalNumberOfRecordingsChosen
Indicates the usual or standard number of recordings that are selected in a given context or process.
-
C.
numberOfSongs
Indicates the quantity of songs associated with a given entity.
-
D.
recordingOf
Indicates that one entity is an audio or video capture or performance that documents, represents, or preserves another entity (such as a work, event, or expression).
-
E.
typicalRecordingDuration
Indicates the usual or standard length of time that something is recorded.
- F. None of above.
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_69ca83529a9c8190b5c075b4f14636ed |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4ae6d19c8190be003f7901c0468d |
completed | March 31, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69cc4567b5c881908d9ec5dcfc783fac |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:32 p.m.