Triple
T26686455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maurice A. Deane School of Law |
E672757
|
entity |
| Predicate | offersProfessionalEducation |
P42231
|
FINISHED |
| Object | legal practice |
—
|
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: legal practice | Statement: [Maurice A. Deane School of Law, offersProfessionalEducation, legal practice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersProfessionalEducation Context triple: [Maurice A. Deane School of Law, offersProfessionalEducation, legal practice]
-
A.
offersProfessionalPrograms
Indicates that an entity provides formal, career-oriented educational or training programs to others.
-
B.
offersEducationIn
chosen
Indicates that an entity provides or delivers educational programs, courses, or instruction in a specified field, subject, or area.
-
C.
offersEducationTo
Indicates that one entity provides educational services, instruction, or learning opportunities to another entity.
-
D.
offersContinuingEducation
Indicates that an entity provides ongoing educational or professional development opportunities to another entity.
-
E.
offersFieldEducation
Indicates that one entity provides practical, field-based educational or training opportunities to another.
- 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_69eecda2066c8190a344218afa5e89c1 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 27, 2026, 3:23 a.m.