Triple
T12928604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Rainicorn |
E309309
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Jake the Dog |
E309302
|
NE 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: Jake the Dog | Statement: [Lady Rainicorn, spouse, Jake the Dog]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jake the Dog Context triple: [Lady Rainicorn, spouse, Jake the Dog]
-
A.
Jake the Dog
chosen
Jake the Dog is a magical, shape-shifting dog and one of the two main protagonists of the animated television series Adventure Time.
-
B.
Piper the Dog
Piper the Dog is the costumed canine mascot representing Hamline University at its athletic events and campus activities.
-
C.
Jack the dog
Jack the dog is a fictional canine character appearing in the animated television series "The Artist."
-
D.
Jake the Peg
"Jake the Peg" is a novelty song and comedic performance piece, popularized by entertainer Rolf Harris, about a man humorously claiming to have an extra leg.
-
E.
Danny Dog
Danny Dog is a playful, friendly puppy character from the children's animated series "Peppa Pig," known for his love of pirates and adventure.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971ec72a48190aceef10630603d2c |
completed | April 10, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1af38248190a85d0fa3a26c3d08 |
completed | May 6, 2026, 8:16 p.m. |
Created at: April 9, 2026, 5:42 p.m.