Triple
T25051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annenberg School for Communication |
E499
|
entity |
| Predicate | educationalLevel |
P177
|
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: [Annenberg School for Communication, educationalLevel, graduate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educationalLevel Context triple: [Annenberg School for Communication, educationalLevel, graduate]
-
A.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
B.
educationType
chosen
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
C.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
D.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
E.
educationSystem
Indicates the relationship in which an entity is part of, governed by, or operates within a particular system or structure of education.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246d794448190bb2844fcd0538eaa |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24657635881908f3415bc1bdfa1b5 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.