Triple
T28513219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lev Gonick |
E721545
|
entity |
| Predicate | educationSectorActivity |
P171001
|
FINISHED |
| Object | modernizing campus IT infrastructure |
—
|
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: modernizing campus IT infrastructure | Statement: [Lev Gonick, educationSectorActivity, modernizing campus IT infrastructure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educationSectorActivity Context triple: [Lev Gonick, educationSectorActivity, modernizing campus IT infrastructure]
-
A.
educationalSector
Indicates a relationship in which something is part of, associated with, or operates within the education or schooling domain.
-
B.
educationSectorStatus
Indicates the condition or state of the education sector in relation to a given context or time.
-
C.
educatesForSector
Indicates that an entity provides education or training specifically aimed at preparing individuals for a particular sector or industry.
-
D.
educationRight
Indicates that an entity holds a right or entitlement to receive education or educational opportunities.
-
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. 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_69f01a5c072081908c7b04bcf6478da9 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6984bb55c8190862eb8796868d188 |
completed | May 3, 2026, 12:35 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 28, 2026, 3:14 a.m.