Triple
T17910462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beach City |
E447805
|
entity |
| Predicate | homeOfCharacter |
P107735
|
FINISHED |
| Object | Connie Maheswaran |
—
|
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: Connie Maheswaran | Statement: [Beach City, homeOfCharacter, Connie Maheswaran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Connie Maheswaran Context triple: [Beach City, homeOfCharacter, Connie Maheswaran]
-
A.
Connie Maheswaran
chosen
Connie Maheswaran is a central human character in the animated series "Steven Universe," known as Steven's close friend and eventual sword-wielding ally.
-
B.
Julie Ganapathi
Julie Ganapathi is a Tamil psychological thriller film directed by Balu Mahendra, known for its intense character study and suspenseful narrative.
-
C.
Loveleen Tandan
Loveleen Tandan is an Indian film director and casting director best known for her co-directing work on the Academy Award–winning film "Slumdog Millionaire."
-
D.
Maya Banerjee
Maya Banerjee is known as the wife of Indian actor Victor Banerjee.
-
E.
Annet Mahendru
Annet Mahendru is an American actress best known for her acclaimed role as Nina Sergeevna Krilova on the television series "The Americans."
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49ea017d081908be850a39edf601f |
completed | April 19, 2026, 9:21 a.m. |
Created at: April 10, 2026, 10:19 a.m.