Triple
T14373708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Characters Edition John Lennon |
E356418
|
entity |
| Predicate | subjectOccupationHonored |
P18120
|
FINISHED |
| Object | musician |
—
|
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: musician | Statement: [Great Characters Edition John Lennon, subjectOccupationHonored, musician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectOccupationHonored Context triple: [Great Characters Edition John Lennon, subjectOccupationHonored, musician]
-
A.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
B.
honouredPersonOccupation
chosen
Indicates that the honored person is or was associated with a particular occupation or professional role.
-
C.
representedOccupation
Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
-
D.
dedicatedToOccupation
Indicates that an entity is committed or devoted to performing or pursuing a particular occupation or professional role.
-
E.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9007184c8190aebb003cb6548cc8 |
completed | April 14, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:15 a.m.