Triple
T2517685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rick Dalton |
E55449
|
entity |
| Predicate | professionStatus |
P24370
|
FINISHED |
| Object | fading star |
—
|
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: fading star | Statement: [Rick Dalton, professionStatus, fading star]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionStatus Context triple: [Rick Dalton, professionStatus, fading star]
-
A.
careerStatus
chosen
Indicates the current stage, position, or condition of an entity within its professional or occupational life.
-
B.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
C.
professionalStatusRestriction
Indicates a limitation or condition placed on someone’s professional role, eligibility, or activities.
-
D.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
E.
memberProfession
Indicates that a member or individual holds or practices a particular profession or occupation.
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0bf37c0819088d28b5081ba7556 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.