Triple
T37812405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devil May Hare |
E942680
|
entity |
| Predicate | hasSpeciesCharacter |
P198841
|
FINISHED |
| Object | anthropomorphic rabbit |
—
|
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: anthropomorphic rabbit | Statement: [Devil May Hare, hasSpeciesCharacter, anthropomorphic rabbit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeciesCharacter Context triple: [Devil May Hare, hasSpeciesCharacter, anthropomorphic rabbit]
-
A.
hasSpeciesRole
Indicates that an entity plays a specific functional or categorical role within a particular species.
-
B.
hasFlagshipSpecies
Indicates that one entity (typically a site, region, or conservation program) is associated with or represented by a particular flagship species used to promote awareness or protection.
-
C.
hasSpeciesRelation
Indicates a biological or taxonomic relationship between entities based on their species classification.
-
D.
belongsToSpecies
Indicates that an individual organism is a member of, or classified under, a particular biological species.
-
E.
hasOnlySpecies
Indicates that an entity is associated exclusively with a single specified species and no others.
- 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_69f76ee8104c8190ab17133ccd8f86e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ff0d80c0dc81909fbd12285c7a45c0 |
completed | May 9, 2026, 10:33 a.m. |
| PD | Predicate disambiguation | batch_69ff0cd03e78819094895058f925fbfa |
completed | May 9, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69ff0d800ee88190835e233d9e846cdb |
completed | May 9, 2026, 10:33 a.m. |
Created at: May 3, 2026, 4:19 p.m.