Triple
T18405314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Resources and Environmental Engineering |
E450107
|
entity |
| Predicate | educatesStudentsIn |
P335
|
FINISHED |
| Object | resources engineering |
—
|
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: resources engineering | Statement: [Department of Resources and Environmental Engineering, educatesStudentsIn, resources engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educatesStudentsIn Context triple: [Department of Resources and Environmental Engineering, educatesStudentsIn, resources engineering]
-
A.
educates
chosen
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
B.
usesStudentsFor
Indicates that one entity employs or exploits students as a resource or means to carry out its activities or achieve its objectives.
-
C.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
D.
educationSystem
Indicates the relationship in which an entity is part of, governed by, or operates within a particular system or structure of education.
-
E.
educationUse
Indicates the use or application of something specifically for educational purposes or in an educational context.
- 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_69d8b9fab8a8819086a9ddc0871715e0 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e51956b8c88190b863e66871825014 |
completed | April 19, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e469bf7f74819096a01173493412c2 |
completed | April 19, 2026, 5:35 a.m. |
Created at: April 10, 2026, 10:46 a.m.