Triple
T1086069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master in Veterinary Medicine |
E24052
|
entity |
| Predicate | includesTopics |
P24066
|
FINISHED |
| Object | diagnostic imaging |
—
|
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: diagnostic imaging | Statement: [Master in Veterinary Medicine, includesTopics, diagnostic imaging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesTopics Context triple: [Master in Veterinary Medicine, includesTopics, diagnostic imaging]
-
A.
includes
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
B.
includesClause
Indicates that one entity (typically a document, contract, or statement) contains or incorporates a specific clause as part of its content.
-
C.
includedWith
Indicates that one entity is provided or packaged together as part of another entity.
-
D.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
E.
frequentlyDiscussedIn
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b963161081908a523c8d63871652 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7407914819092ed933a7316b450 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b8f1097881908932d7eea4331917 |
completed | March 1, 2026, 10:08 p.m. |
Created at: March 1, 2026, 7:42 p.m.