Triple
T37958055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Louis Stevenson Trail |
E946920
|
entity |
| Predicate | hasAssociatedAnimalInNarrative |
P51902
|
FINISHED |
| Object | donkey |
—
|
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: donkey | Statement: [Robert Louis Stevenson Trail, hasAssociatedAnimalInNarrative, donkey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedAnimalInNarrative Context triple: [Robert Louis Stevenson Trail, hasAssociatedAnimalInNarrative, donkey]
-
A.
associatedWithAnimal
chosen
Indicates a relationship where an entity has a connection, link, or relevance to an animal.
-
B.
hasAnimal
Indicates that one entity possesses, keeps, or is associated with an animal.
-
C.
hasAnimalRoleType
Indicates that an entity holds or is assigned a specific role or function in relation to an animal.
-
D.
hasAnimalActor
Indicates that an animal serves as the acting agent or performer in the specified event or relationship.
-
E.
hasPartInNarrative
Indicates that one entity plays a role or participates as a component within the storyline or structure of another narrative entity.
- 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_69f76ef7062c819091bfacb7e83aa1e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd864235b481908738dbb69556bc62 |
completed | May 8, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_69fd8373b6bc819091c554f29ee17fec |
completed | May 8, 2026, 6:32 a.m. |
Created at: May 3, 2026, 4:20 p.m.