Triple
T16183733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiran Rao |
E392746
|
entity |
| Predicate | produced |
P490
|
FINISHED |
| Object | Dhobi Ghat |
E1199437
|
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: Dhobi Ghat | Statement: [Kiran Rao, produced, Dhobi Ghat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dhobi Ghat Context triple: [Kiran Rao, produced, Dhobi Ghat]
-
A.
Dhobi Ghat
chosen
Dhobi Ghat is a 2010 Indian drama film set in Mumbai that interweaves the lives of four characters to explore themes of urban loneliness and connection.
-
B.
Vishram Ghat
Vishram Ghat is a prominent riverside bathing and pilgrimage site in Mathura, India, revered in Hindu tradition as the place where Lord Krishna is believed to have rested after defeating the tyrant Kamsa.
-
C.
Gandhi Bazaar
Gandhi Bazaar is a historic and bustling commercial market area in Bengaluru, India, known for its traditional shops, eateries, and vibrant street life.
-
D.
Sadarghat
Sadarghat is one of the busiest river ports in Bangladesh, serving as a major hub for passenger and cargo transport on the Buriganga River in Dhaka.
-
E.
Palika Bazaar
Palika Bazaar is a large underground market in New Delhi, India, known for its wide range of inexpensive goods and bustling atmosphere.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205fc080819097858f36253fef7c |
completed | April 17, 2026, 11:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ecd897c81908cbea306c9f95da3 |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:02 a.m.