Triple
T16146979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max (the dog) |
E391808
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Stella (dog actor) |
E1050565
|
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: Stella (dog actor) | Statement: [Max (the dog), portrayedBy, Stella (dog actor)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stella (dog actor) Context triple: [Max (the dog), portrayedBy, Stella (dog actor)]
-
A.
Stella (family dog, indirectly)
chosen
Stella is the Delgado-Pritchett family’s beloved French bulldog on the television series "Modern Family," known for her close bond with Jay and frequent comedic moments.
-
B.
Elizabeth Taylor (dog)
Elizabeth Taylor is Charlotte York's beloved Cavalier King Charles Spaniel from the television series "Sex and the City."
-
C.
Beasley the Dog
Beasley the Dog was the canine actor best known for playing the slobbery Dogue de Bordeaux partner to Tom Hanks in the 1989 film "Turner & Hooch."
-
D.
Stella
Stella is a character from the animated series "The Collection," known for her central role in the show's unfolding mysteries and interpersonal drama.
-
E.
Stella
Stella is a key character in Guy Ritchie's crime film "RocknRolla," known as a sharp, stylish accountant entangled in the London underworld.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d947e68819081b4b7c757ce71b6 |
completed | April 17, 2026, 11:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7a7dc3481909f933acd72d6feff |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:01 a.m.