Triple
T19493959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Large Animal Hospital |
E487721
|
entity |
| Predicate | treatsAnimalType |
P97103
|
FINISHED |
| Object | horses |
—
|
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: horses | Statement: [Large Animal Hospital, treatsAnimalType, horses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsAnimalType Context triple: [Large Animal Hospital, treatsAnimalType, horses]
-
A.
animalTypeServed
chosen
Indicates the type or category of animal that is provided or served in a given context.
-
B.
animalTypeFeatured
Indicates that a particular type or category of animal is highlighted or prominently showcased in a given context.
-
C.
companionAnimals
Indicates a relationship where one entity keeps or cares for another entity as a pet or companion animal.
-
D.
speciesType
Indicates the specific biological species category to which an entity belongs.
-
E.
knownForTreatmentOf
Indicates that an entity is recognized or notable for providing treatment or medical care for a particular condition, disease, or type of patient.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6349002788190afe7831d008d440f |
completed | April 20, 2026, 2:13 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7883308190b73912a71a35a835 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:40 p.m.