Triple
T12391840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mindy Project |
E296011
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Mindy |
E807919
|
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: Mindy | Statement: [The Mindy Project, alsoKnownAs, Mindy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mindy Context triple: [The Mindy Project, alsoKnownAs, Mindy]
-
A.
Mindy
chosen
Mindy is a feminine given name most notably associated with American actress Mindy Cohn, known for her role on the TV series "The Facts of Life."
-
B.
Mindy Sterling
Mindy Sterling is an American actress and comedian best known for her role as the villainous Frau Farbissina in the Austin Powers film series.
-
C.
June Mindy
June Mindy is a fictional character in the film "Don't Look Up," portrayed as the wife of astronomer Dr. Randall Mindy.
-
D.
Mandie
Mandie is a feminine given name, typically used as a variant spelling of Mandy or Amanda.
-
E.
Melinda
Melinda is a central female character in George Farquhar’s Restoration comedy "The Recruiting Officer," known for her wit, independence, and role in the play’s romantic intrigues.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fd0bcc48190bb1a59a3aaa6bfdf |
completed | April 10, 2026, 6:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6347c239881909a031e9e195080c9 |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:54 p.m.