Triple
T12904302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judah P. Benjamin |
E308691
|
entity |
| Predicate | studiedLawBy |
P107370
|
FINISHED |
| Object | reading law |
—
|
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: reading law | Statement: [Judah P. Benjamin, studiedLawBy, reading law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studiedLawBy Context triple: [Judah P. Benjamin, studiedLawBy, reading law]
-
A.
studiedLawIn
Indicates that a person received legal education or training at a particular institution or location.
-
B.
schoolOfJurisprudence
Indicates that one entity is a legal philosophy, doctrine, or interpretive framework to which the other entity (such as a jurist, decision, or institution) adheres or belongs.
-
C.
lawSchoolName
Indicates the name of the law school with which an entity (such as a person or institution) is associated.
-
D.
hasLegalEducationInstitution
Indicates that an entity is associated with or linked to an institution that provides legal education.
-
E.
majorSchoolOfLaw
Indicates that a particular school of law is a primary or dominant legal tradition or framework associated with an entity.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971831bd48190b0ecd13e7181bbc6 |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9713e45a88190acd346f066093550 |
completed | April 10, 2026, 9:53 p.m. |
Created at: April 9, 2026, 5:40 p.m.