Triple
T3860135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Travels with Charley: In Search of America |
E90113
|
entity |
| Predicate | hasCompanionAnimal |
P24316
|
FINISHED |
| Object | dog |
—
|
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: dog | Statement: [Travels with Charley: In Search of America, hasCompanionAnimal, dog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCompanionAnimal Context triple: [Travels with Charley: In Search of America, hasCompanionAnimal, dog]
-
A.
hasAnimal
Indicates that one entity possesses, keeps, or is associated with an animal.
-
B.
companionAnimals
chosen
Indicates a relationship where one entity keeps or cares for another entity as a pet or companion animal.
-
C.
hasAnimalCollection
Indicates that one entity possesses or maintains a collection or group of animals associated with it.
-
D.
hasPetOwner
Indicates that a person or entity serves as the owner or caretaker of a particular pet.
-
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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec212a1c8190aba6311630c3fd3e |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.