Triple
T3603097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terriers |
E76302
|
entity |
| Predicate | hasAssociationWithAnimal |
P13551
|
FINISHED |
| Object | Boston Terrier dog breed |
—
|
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: Boston Terrier dog breed | Statement: [Terriers, hasAssociationWithAnimal, Boston Terrier dog breed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociationWithAnimal Context triple: [Terriers, hasAssociationWithAnimal, Boston Terrier dog breed]
-
A.
hasAnimal
chosen
Indicates that one entity possesses, keeps, or is associated with an animal.
-
B.
hasAnimalCollection
Indicates that one entity possesses or maintains a collection or group of animals associated with it.
-
C.
usesLiveAnimals
Indicates that one entity employs or incorporates live animals in performing an action, service, process, or activity involving another entity.
-
D.
usedAnimal
Indicates that one entity employed or exploited an animal for a particular purpose or activity.
-
E.
hasPetInterest
Indicates that one entity has an interest in, affinity for, or concern about pets in relation to another entity or context.
- 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_69ad85d93dcc819094fba90cf70f4996 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc1df08a48190a4a4a20c8821b321 |
completed | March 8, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69adb83d8b1c8190b3bddbc5dc995a87 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:22 p.m.