Triple
T20223751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helga Hufflepuff |
E495322
|
entity |
| Predicate | houseAnimalAssociated |
P51902
|
FINISHED |
| Object | badger |
—
|
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: badger | Statement: [Helga Hufflepuff, houseAnimalAssociated, badger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: houseAnimalAssociated Context triple: [Helga Hufflepuff, houseAnimalAssociated, badger]
-
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.
hasAnimal
Indicates that one entity possesses, keeps, or is associated with an animal.
-
D.
animalTypeLoved
Indicates that one entity loves or is especially fond of animals of a particular type.
-
E.
associatedWithAnimal
chosen
Indicates a relationship where an entity has a connection, link, or relevance to an animal.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fd827708190b798a30f4e7d533f |
completed | April 20, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69e55b18609481909ab28bc8750a642f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:39 p.m.