Triple
T22757476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunil Sukthankar |
E562888
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Kaasav
Kaasav is a critically acclaimed Marathi-language film that sensitively explores mental health and human relationships, co-directed by Sunil Sukthankar and Sumitra Bhave.
|
E1554227
|
NE FINISHED |
How this triple was built (4 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: Kaasav | Statement: [Sunil Sukthankar, notableWork, Kaasav]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaasav Context triple: [Sunil Sukthankar, notableWork, Kaasav]
-
A.
Kasavakan
Kasavakan is a village in Taiwan associated with the Puyuma Indigenous people, where the Puyuma language is traditionally spoken.
-
B.
Kaikesi
Kaikesi is a figure in the Hindu epic Ramayana, known as the rakshasi queen of Lanka and the mother of Ravana, Kumbhakarna, and Vibhishana.
-
C.
Kösseine
Kösseine is a prominent granite mountain in northeastern Bavaria, Germany, known for its scenic views and hiking trails within the Fichtel Mountains.
-
D.
Kaskelen
Kaskelen is a town in southeastern Kazakhstan that serves as a local center within the Almaty Region, situated near the city of Almaty.
-
E.
Laak
Laak is an urban district of The Hague in the Netherlands, known for its dense residential areas, canals, and diverse population.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kaasav Triple: [Sunil Sukthankar, notableWork, Kaasav]
Generated description
Kaasav is a critically acclaimed Marathi-language film that sensitively explores mental health and human relationships, co-directed by Sunil Sukthankar and Sumitra Bhave.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kaasav Target entity description: Kaasav is a critically acclaimed Marathi-language film that sensitively explores mental health and human relationships, co-directed by Sunil Sukthankar and Sumitra Bhave.
-
A.
Kasavakan
Kasavakan is a village in Taiwan associated with the Puyuma Indigenous people, where the Puyuma language is traditionally spoken.
-
B.
Kaikesi
Kaikesi is a figure in the Hindu epic Ramayana, known as the rakshasi queen of Lanka and the mother of Ravana, Kumbhakarna, and Vibhishana.
-
C.
Kösseine
Kösseine is a prominent granite mountain in northeastern Bavaria, Germany, known for its scenic views and hiking trails within the Fichtel Mountains.
-
D.
Kaskelen
Kaskelen is a town in southeastern Kazakhstan that serves as a local center within the Almaty Region, situated near the city of Almaty.
-
E.
Laak
Laak is an urban district of The Hague in the Netherlands, known for its dense residential areas, canals, and diverse population.
- F. None of above. chosen
Provenance (5 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17a798ae08190b9810bf241613198 |
completed | April 29, 2026, 3:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b98150cfc8190a3530e51f0311e33 |
completed | May 18, 2026, 10:52 p.m. |
| NEDg | Description generation | batch_6a0b99f7ee848190a4838e757cff7de6 |
completed | May 18, 2026, 11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b9ab1cb508190befa17184bfd8f51 |
completed | May 18, 2026, 11:03 p.m. |
Created at: April 17, 2026, 3:25 p.m.