Triple
T606752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cynicism |
E12009
|
entity |
| Predicate | regardsDogsAs |
P17031
|
FINISHED |
| Object | models of natural living |
—
|
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: models of natural living | Statement: [Cynicism, regardsDogsAs, models of natural living]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regardsDogsAs Context triple: [Cynicism, regardsDogsAs, models of natural living]
-
A.
pet
Indicates that one entity keeps another animal for companionship or pleasure, typically providing care and shelter.
-
B.
hasAnimal
Indicates that one entity possesses, keeps, or is associated with an animal.
-
C.
usedAnimal
Indicates that one entity employed or exploited an animal for a particular purpose or activity.
-
D.
notableDomesticatedSpecies
Indicates that the subject is a species that is particularly well-known or significant as a domesticated animal.
-
E.
numberOfAnimals
Indicates the quantity of animals associated with a given entity 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df34abc8190a578c8c2ab3d28e4 |
completed | March 1, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69a49cf8fc1c81908a9c7df552aa1a59 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49def31ec81909dc53e70f4a36eda |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.