Triple
T23820827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellen Rosenblum |
E589231
|
entity |
| Predicate | legalCareerType |
P153756
|
FINISHED |
| Object | public service |
—
|
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: public service | Statement: [Ellen Rosenblum, legalCareerType, public service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalCareerType Context triple: [Ellen Rosenblum, legalCareerType, public service]
-
A.
legalProfessionType
Indicates the specific category or type of legal profession associated with an entity (such as lawyer, judge, or notary).
-
B.
legalProfessionIncludes
Indicates that a legal profession or role encompasses, involves, or includes another specified legal function, specialization, or activity.
-
C.
legalProfessionRole
Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
-
D.
legalProfessionTypeRegulated
Indicates that the specified type of legal profession is subject to formal regulation or oversight by an authority.
-
E.
legalPractice
Indicates a relationship where an entity engages in or is associated with the professional provision of legal services or the practice of law.
- F. None of above. chosen
Provenance (4 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_69e25d18619081909c7fb89d8926f14a |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c7af4d4481908095348fae9e54f4 |
completed | April 29, 2026, 8:56 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f158b0e320819090b947ee7eb14116 |
completed | April 29, 2026, 1:02 a.m. |
Created at: April 17, 2026, 7:59 p.m.