Triple
T16253612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Call Jane |
E394574
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Roshan Sethi |
E1015758
|
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: Roshan Sethi | Statement: [Call Jane, screenwriter, Roshan Sethi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roshan Sethi Context triple: [Call Jane, screenwriter, Roshan Sethi]
-
A.
Roshan Sethi
chosen
Roshan Sethi is a physician-turned-screenwriter and television producer best known for co-creating the medical drama series "The Resident."
-
B.
Asoka Mehta
Asoka Mehta was an Indian socialist leader, freedom fighter, and prominent politician known for his key role in shaping socialist thought and policy within India’s early post-independence politics.
-
C.
Zaab Sethna
Zaab Sethna is a public relations and communications professional best known as the husband of actress Gina Bellman.
-
D.
Sanjay Suri
Sanjay Suri is an Indian actor and film producer known for his work in Hindi cinema and independent films.
-
E.
Roshan Seth
Roshan Seth is an Indian-born British actor known for his character roles in films such as "Gandhi," "Indiana Jones and the Temple of Doom," and numerous British and international productions.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24598c9488190a92df7d8b1824724 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004571013c8190ae3e4ecd17c08004 |
completed | May 10, 2026, 8:44 a.m. |
Created at: April 10, 2026, 5:04 a.m.