Triple
T2528323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Radcliffe |
E56091
|
entity |
| Predicate | employedIn |
P17879
|
FINISHED |
| Object | publishing industry of late 18th-century England |
—
|
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: publishing industry of late 18th-century England | Statement: [William Radcliffe, employedIn, publishing industry of late 18th-century England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employedIn Context triple: [William Radcliffe, employedIn, publishing industry of late 18th-century England]
-
A.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
B.
employedApproximately
Indicates that one entity employs another in a manner where the number, duration, or extent of employment is approximate rather than exact.
-
C.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
D.
workedAs
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
-
E.
hasWorkedIn
chosen
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd257ea908190a010c0b785853546 |
completed | March 7, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69abd0c2e34c8190a914d5c2afba147c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.