Triple
T6837305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Lassell |
E157481
|
entity |
| Predicate | otherOccupation |
P2374
|
FINISHED |
| Object | brewer |
—
|
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: brewer | Statement: [William Lassell, otherOccupation, brewer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherOccupation Context triple: [William Lassell, otherOccupation, brewer]
-
A.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
B.
otherWork
Indicates that one work is related to another work by the same creator, but is distinct from the primary or referenced work.
-
C.
traditionalOccupations
Indicates that an entity is associated with occupations or jobs that are customary, long-established, or culturally traditional within a particular community or context.
-
D.
recipientOccupation
Indicates that the object specifies the job, profession, or role held by the recipient in the described relationship or event.
-
E.
sponsorOccupation
Indicates that one entity serves as the occupation or professional role of a sponsor associated with another entity.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d67db4008190b86b497bf6f0c73a |
completed | March 27, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c6d09f90648190bc0a462c7d59de1b |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:19 p.m.