Triple
T9854821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weeds |
E239556
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Maulik Pancholy |
E227335
|
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: Maulik Pancholy | Statement: [Weeds, starring, Maulik Pancholy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maulik Pancholy Context triple: [Weeds, starring, Maulik Pancholy]
-
A.
Maulik Pancholy
chosen
Maulik Pancholy is an American actor and author best known for his comedic television roles, including his portrayal of Jonathan on the sitcom "30 Rock."
-
B.
Nick Mehta
Nick Mehta is a technology executive best known as the CEO of Gainsight and a prominent advocate and thought leader in the field of customer success.
-
C.
Aditya Ramesh
Aditya Ramesh is a computer scientist and AI researcher best known for leading the development of OpenAI’s CLIP and DALL·E models.
-
D.
Kumail Nanjiani
Kumail Nanjiani is a Pakistani-American comedian, actor, and writer best known for his stand-up work, his role on the TV series "Silicon Valley," and co-writing and starring in the film "The Big Sick."
-
E.
Vishal Amin
Vishal Amin is a U.S. intellectual property policy official who served as the White House Intellectual Property Enforcement Coordinator, overseeing federal efforts to combat IP infringement.
- 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3960fb481909c90d6d6cafc6222 |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5f21a04819099f23ede55ec3417 |
completed | April 5, 2026, 3:24 a.m. |
Created at: March 30, 2026, 8:34 p.m.