Triple
T21944547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunday |
E541901
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Ranveer Singh |
—
|
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: Ranveer Singh | Statement: [Gunday, castMember, Ranveer Singh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ranveer Singh Context triple: [Gunday, castMember, Ranveer Singh]
-
A.
Ranveer Singh
chosen
Ranveer Singh is a popular Indian film actor known for his energetic performances and leading roles in numerous successful Bollywood movies.
-
B.
Ranbir Kapoor
Ranbir Kapoor is a prominent Indian film actor and producer known for his leading roles in contemporary Hindi cinema.
-
C.
Ranbir Singh
Ranbir Singh was a 19th-century Maharaja of Jammu and Kashmir known for consolidating Dogra rule and promoting administrative, legal, and educational reforms in the princely state.
-
D.
Rajkummar Rao
Rajkummar Rao is an acclaimed Indian film actor known for his versatile performances in Hindi cinema, particularly in critically praised independent and mainstream films.
-
E.
Varun Dhawan
Varun Dhawan is a popular Indian film actor known for his work in contemporary Bollywood cinema, particularly in commercial comedies and dramas.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242688988190a7b8f033c49368de |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:56 p.m.