Triple
T16044620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Roth |
E389183
|
entity |
| Predicate | hasPetOrAnimalCompanion |
P22866
|
FINISHED |
| Object | marine animals at the aquarium |
—
|
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: marine animals at the aquarium | Statement: [Henry Roth, hasPetOrAnimalCompanion, marine animals at the aquarium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPetOrAnimalCompanion Context triple: [Henry Roth, hasPetOrAnimalCompanion, marine animals at the aquarium]
-
A.
hasAnimal
Indicates that one entity possesses, keeps, or is associated with an animal.
-
B.
hasAnimalCollection
chosen
Indicates that one entity possesses or maintains a collection or group of animals associated with it.
-
C.
associatedWithAnimal
Indicates a relationship where an entity has a connection, link, or relevance to an animal.
-
D.
hasPetOwner
Indicates that a person or entity serves as the owner or caretaker of a particular pet.
-
E.
companionAnimals
Indicates a relationship where one entity keeps or cares for another entity as a pet or companion 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1826f34c081908005bb736f1c485d |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.