Triple
T23152966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tallulah |
E578367
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Eleanor Columbus |
—
|
NE NERFINISHED |
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: Eleanor Columbus | Statement: [Tallulah, producer, Eleanor Columbus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eleanor Columbus Context triple: [Tallulah, producer, Eleanor Columbus]
-
A.
Eleanor Columbus
chosen
Eleanor Columbus is an American actress and producer known for her small roles in films directed by her father, filmmaker Chris Columbus, including the Harry Potter series.
-
B.
Isabella Columbus
Isabella Columbus was a daughter of Christopher Joseph Columbus, a descendant of the famed explorer Christopher Columbus.
-
C.
Isabella Colón
Isabella Colón is a fictional character from the legal drama television series "Bull," where she serves as a key member of Dr. Jason Bull’s trial consulting team.
-
D.
Violet Columbus
Violet Columbus is an American actress and filmmaker known for her work in independent films and for being the daughter of director Chris Columbus.
-
E.
Martha Cristiana
Martha Cristiana is a Mexican actress and model best known for her work in telenovelas and fashion campaigns.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18efaa1fc81908fb1987dbf732f46 |
completed | April 29, 2026, 4:54 a.m. |
Created at: April 17, 2026, 4:01 p.m.