Triple
T15784733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antarctica: Empire of the Penguin |
E382706
|
entity |
| Predicate | subjectHasAnimal |
P13551
|
FINISHED |
| Object | penguin |
—
|
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: penguin | Statement: [Antarctica: Empire of the Penguin, subjectHasAnimal, penguin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectHasAnimal Context triple: [Antarctica: Empire of the Penguin, subjectHasAnimal, penguin]
-
A.
hasAnimal
chosen
Indicates that one entity possesses, keeps, or is associated with an animal.
-
B.
associatedWithAnimal
Indicates a relationship where an entity has a connection, link, or relevance to an animal.
-
C.
hasAnimalActor
Indicates that an animal serves as the acting agent or performer in the specified event or relationship.
-
D.
hasAnimalCollection
Indicates that one entity possesses or maintains a collection or group of animals associated with it.
-
E.
hasPetInterest
Indicates that one entity has an interest in, affinity for, or concern about pets in relation to another entity or context.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05401c4788190a31c180953433db9 |
completed | April 16, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.