Triple
T5321269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canis lupus familiaris |
E121677
|
entity |
| Predicate | variationIncludes |
P1393
|
FINISHED |
| Object | size diversity among breeds |
—
|
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: size diversity among breeds | Statement: [Canis lupus familiaris, variationIncludes, size diversity among breeds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: variationIncludes Context triple: [Canis lupus familiaris, variationIncludes, size diversity among breeds]
-
A.
variant
Indicates that one entity is an alternative form, version, or variation of another entity.
-
B.
compositionVariesBy
Indicates that the composition of something differs depending on a specified factor, condition, or context.
-
C.
varietyOf
Indicates that one entity is a specific type, kind, or variant of another, more general entity.
-
D.
variantCount
Indicates the number of distinct variants associated with a given entity or item.
-
E.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd86f20f008190be7b5848af05f2b8 |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd84561c7081909e5937c7816e492c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 1:59 p.m.