Triple
T16685711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satish Kaushik |
E405456
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Satish |
E403038
|
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: Satish | Statement: [Satish Kaushik, givenName, Satish]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Satish Context triple: [Satish Kaushik, givenName, Satish]
-
A.
Satish Alekar
Satish Alekar is a prominent Indian playwright, actor, and director known for his innovative and influential contributions to modern Marathi theatre.
-
B.
Sanjay
Sanjay is the given name of Sanjay Gandhi, an influential and controversial Indian politician and son of former Prime Minister Indira Gandhi.
-
C.
Subhash
Subhash is one of the central protagonists of Jhumpa Lahiri’s novel "The Lowland," depicted as a thoughtful, reserved brother whose life diverges sharply from his more radical sibling’s amid political turmoil in India.
-
D.
Harish
Harish is the given name of Harish-Chandra, a prominent Indian-American mathematician and physicist known for his foundational work in representation theory.
-
E.
Satish Shah
chosen
Satish Shah is an Indian actor best known for his comic roles in Hindi films and television, particularly in popular sitcoms like "Yeh Jo Hai Zindagi" and "Sarabhai vs Sarabhai."
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ea550c0819085bd36c44237a61a |
completed | April 18, 2026, 12:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a43f6a08190913ca123a2377f95 |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.