Triple
T32398361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Fang 2: Myth of the White Wolf |
E827872
|
entity |
| Predicate | hasSpeciesOfMainAnimal |
P49509
|
FINISHED |
| Object | wolfdog |
—
|
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: wolfdog | Statement: [White Fang 2: Myth of the White Wolf, hasSpeciesOfMainAnimal, wolfdog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeciesOfMainAnimal Context triple: [White Fang 2: Myth of the White Wolf, hasSpeciesOfMainAnimal, wolfdog]
-
A.
hasAnimal
Indicates that one entity possesses, keeps, or is associated with an animal.
-
B.
hasMammalSpecies
chosen
Indicates that one entity includes, contains, or is associated with a particular mammal species as part of its composition, population, or classification.
-
C.
hasCamelSpecies
Indicates that one entity is a camel and the other specifies the biological species to which that camel belongs.
-
D.
hasLargeSpecies
Indicates that an entity possesses or includes at least one species that is considered large in size.
-
E.
hasAnimalClass
Indicates that an entity belongs to, or is categorized under, a particular animal class (such as mammal, bird, reptile, etc.).
- 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_69f34919342c8190a4c3bf35a90d4e58 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd5f29b1988190877764ef2a399c7f |
completed | May 8, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69fd5e30194c819085b5ce586122ab37 |
completed | May 8, 2026, 3:53 a.m. |
Created at: May 1, 2026, 12:52 a.m.