Triple
T5321268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canis lupus familiaris |
E121677
|
entity |
| Predicate | hasMorphologicalDiversity |
P13845
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Canis lupus familiaris, hasMorphologicalDiversity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMorphologicalDiversity Context triple: [Canis lupus familiaris, hasMorphologicalDiversity, high]
-
A.
hasSynapomorphy
Indicates that two or more taxa share a derived character state inherited from their most recent common ancestor, distinguishing that clade from others.
-
B.
isMostDiverseClassOf
Indicates that one class has the greatest diversity (e.g., in members, attributes, or types) compared to all other classes in a given set.
-
C.
notableMorphology
Indicates that an entity is characterized by a distinctive or noteworthy physical form, structure, or shape.
-
D.
modifiesMorphologyOf
Indicates that one entity alters or changes the morphological structure or form of another entity.
-
E.
hasVariability
chosen
Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
- 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.