Triple
T15636595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Jones |
E375959
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Melissa Rosenberg |
—
|
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: Melissa Rosenberg | Statement: [Jessica Jones, executiveProducer, Melissa Rosenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melissa Rosenberg Context triple: [Jessica Jones, executiveProducer, Melissa Rosenberg]
-
A.
Melissa Rosenberg
chosen
Melissa Rosenberg is an American screenwriter and producer best known for adapting the Twilight Saga films and creating the Marvel television series Jessica Jones.
-
B.
Melissa Schuman
Melissa Schuman is an American singer and actress best known as a member of the girl group Dream and for her roles in early-2000s teen films.
-
C.
Melissa Cohen
Melissa Cohen is a South African-born filmmaker and activist best known as the wife of Hunter Biden, son of U.S. President Joe Biden.
-
D.
Melissa Stark
Melissa Stark is an American television sportscaster best known for her work as a sideline reporter on NFL broadcasts.
-
E.
Rachel Leibowitz
Rachel Leibowitz is a person notable enough to be specifically cited as a bearer of the surname Leibowitz.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eba51f08190ac5d9de7fc89405a |
completed | April 16, 2026, 2:51 a.m. |
Created at: April 10, 2026, 4:14 a.m.