Triple
T2588406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Animal Medical Center of New York |
E58057
|
entity |
| Predicate | educationPrograms |
P2489
|
FINISHED |
| Object | veterinary internships |
—
|
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: veterinary internships | Statement: [Animal Medical Center of New York, educationPrograms, veterinary internships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educationPrograms Context triple: [Animal Medical Center of New York, educationPrograms, veterinary internships]
-
A.
hasEducationalProgram
chosen
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
B.
educationSystem
Indicates the relationship in which an entity is part of, governed by, or operates within a particular system or structure of education.
-
C.
offersEducationTo
Indicates that one entity provides educational services, instruction, or learning opportunities to another entity.
-
D.
educationRight
Indicates that an entity holds a right or entitlement to receive education or educational opportunities.
-
E.
sponsoredPrograms
Indicates that an entity provides financial or resource support to specific programs or initiatives.
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd3fd1d608190a0cf0d12a9e6ce59 |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d19308819089ee942513d567a4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.