Triple
T8428305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She Wolf |
E199055
|
entity |
| Predicate | associatedAnimalImagery |
P41568
|
FINISHED |
| Object | wolf |
—
|
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: wolf | Statement: [She Wolf, associatedAnimalImagery, wolf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAnimalImagery Context triple: [She Wolf, associatedAnimalImagery, wolf]
-
A.
animalAssociation
Indicates a relationship in which one animal is associated with another animal or entity, such as through interaction, co-occurrence, or ecological linkage.
-
B.
companionAnimals
Indicates a relationship where one entity keeps or cares for another entity as a pet or companion animal.
-
C.
animalProtagonist
Indicates that the main character or central figure in a narrative is an animal.
-
D.
animalSymbol
chosen
Indicates that one entity serves as a symbolic representation or emblem of the other in the form of an animal.
-
E.
animalTypeLoved
Indicates that one entity loves or is especially fond of animals of a particular type.
- 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0ec200c8190b0299e2b0b4bdcc2 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:07 p.m.