Triple
T11076183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Equity Court Chambers |
E261870
|
entity |
| Predicate | occupationContext |
P77347
|
FINISHED |
| Object | barristers |
—
|
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: barristers | Statement: [Equity Court Chambers, occupationContext, barristers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationContext Context triple: [Equity Court Chambers, occupationContext, barristers]
-
A.
employmentContext
Indicates the situational or organizational setting in which an employment relationship or work activity takes place.
-
B.
subjectHasOccupationContext
chosen
Indicates that a subject’s occupation is specified or interpreted within a particular contextual framework (such as time, place, or situation).
-
C.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
D.
nationalContextOfWork
Indicates the country or national setting within which the work or activity is carried out.
-
E.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7994fcbc081908ff8f7321c0c5892 |
completed | April 9, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69d74415403c81909778bcd829e8832e |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:26 p.m.