Triple
T35905012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Police Nursing College |
E1038447
|
entity |
| Predicate | educatesForContext |
P55744
|
FINISHED |
| Object | police hospitals |
—
|
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: police hospitals | Statement: [Police Nursing College, educatesForContext, police hospitals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educatesForContext Context triple: [Police Nursing College, educatesForContext, police hospitals]
-
A.
educationalContext
chosen
Indicates the situational or institutional setting in which an educational activity, interaction, or resource takes place.
-
B.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
C.
educationalContent
Indicates that one entity provides or is associated with instructional or learning-oriented material intended to educate another entity.
-
D.
teachesAbout
Indicates that one entity provides instruction or information to another entity on a particular subject or topic.
-
E.
educationalModel
Indicates that one entity serves as an educational model, framework, or paradigm that guides or structures the teaching, learning, or training practices of 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_69f76e2259608190bf6788a132e0d139 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b2c771108190adeec151daad5dab |
completed | May 3, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:07 p.m.