Triple
T23241683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Up Next |
E581465
|
entity |
| Predicate | chronologicalContextInArtistCareer |
P30618
|
FINISHED |
| Object | early career |
—
|
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: early career | Statement: [Up Next, chronologicalContextInArtistCareer, early career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chronologicalContextInArtistCareer Context triple: [Up Next, chronologicalContextInArtistCareer, early career]
-
A.
chronologyOfArtist
Indicates the temporal sequence or timeline of events, works, or periods associated with an artist.
-
B.
chronologyWithinArtistOeuvre
Indicates the temporal ordering of works within a single artist’s body of work, specifying how one piece relates in time to others by the same artist.
-
C.
chronologyInArtistRepertoire
Indicates the temporal order in which works appear within an artist’s repertoire or body of work.
-
D.
basedOnArtistCareerOf
Indicates that something is derived from, inspired by, or conceptually grounded in the professional career or body of work of a particular artist.
-
E.
timeInArtistCareer
chosen
Indicates the point or period within an artist’s professional career at which a given event, work, or activity occurs.
- 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_69e2460556f88190be1744a84a84173f |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f192edd974819093a57456e7b12a03 |
completed | April 29, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69effcdadec0819092ec1749ee453b4e |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:10 p.m.