Triple
T904091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John G. Roberts Jr. |
E19507
|
entity |
| Predicate | clerkship |
P20217
|
FINISHED |
| Object | Clerk to Justice William H. Rehnquist |
—
|
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: Clerk to Justice William H. Rehnquist | Statement: [John G. Roberts Jr., clerkship, Clerk to Justice William H. Rehnquist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clerkship Context triple: [John G. Roberts Jr., clerkship, Clerk to Justice William H. Rehnquist]
-
A.
establishedAsClinicalSchool
Indicates that an institution or facility has been formally designated and recognized as a clinical school for education and training purposes.
-
B.
practicedLawIn
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
C.
practiceType
Indicates the specific kind or category of practice associated with an entity or activity.
-
D.
practice
Indicates that an entity regularly performs an activity or skill, typically to improve proficiency or maintain competence.
-
E.
hasClerk
Indicates that an entity is served, assisted, or managed by a clerk associated with it.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad58334881908df191140b786780 |
completed | March 1, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69a4aa98caec8190bbcc38320090f058 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab60fea8819098ce3269181897d1 |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:39 p.m.