Triple
T17040180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northeastern University School of Law buildings |
E413423
|
entity |
| Predicate | servesAcademicLevel |
P19022
|
FINISHED |
| Object | graduate |
—
|
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: graduate | Statement: [Northeastern University School of Law buildings, servesAcademicLevel, graduate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesAcademicLevel Context triple: [Northeastern University School of Law buildings, servesAcademicLevel, graduate]
-
A.
servesGradeLevels
Indicates that an entity (such as a school or program) provides services or instruction to students in the specified grade levels.
-
B.
taughtAtLevel
Indicates that an entity provided instruction or teaching at a specified level of education, difficulty, or proficiency.
-
C.
eligibleGradeLevels
Indicates the grade levels for which something (such as a program, course, or benefit) is considered eligible or applicable.
-
D.
eligibilityGradeLevel
Indicates the grade level or range of grade levels for which an entity is considered eligible or appropriate.
-
E.
supportsLevelOfStudy
chosen
Indicates that one entity provides or is compatible with a specified level of academic or educational study for another entity.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f5844c819097eade4a2b42ab91 |
completed | April 18, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.