Triple
T17978807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Veterinary Medical Association Council on Education |
E449545
|
entity |
| Predicate | meetsNeedOf |
P129980
|
FINISHED |
| Object | veterinary profession |
—
|
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 profession | Statement: [American Veterinary Medical Association Council on Education, meetsNeedOf, veterinary profession]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetsNeedOf Context triple: [American Veterinary Medical Association Council on Education, meetsNeedOf, veterinary profession]
-
A.
meets
Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
-
B.
meetsOnDemandOf
Indicates that one entity meets another specifically in response to a request or demand made by that other entity.
-
C.
meetsTo
Indicates that one entity comes together with another at a specific time and place for an encounter, appointment, or interaction.
-
D.
mustMeet
Indicates that one entity is required or obligated to have a meeting or encounter with another entity.
-
E.
meetsType
Indicates that one entity encounters or comes into contact with another entity in a particular manner or context.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b201d1508190a9d6abbfd04bdcae |
completed | April 19, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e3f8fa62688190a5d5c361ab896256 |
completed | April 18, 2026, 9:34 p.m. |
| PDg | Predicate description generation | batch_69e42d8d68288190a05dc5d7803cf823 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:22 a.m.