Triple
T1023875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vijay Tendulkar |
E22095
|
entity |
| Predicate | screenwriterOf |
P2831
|
FINISHED |
| Object |
Akrosh
Akrosh is an Indian film best known as a hard-hitting social drama written by acclaimed playwright and screenwriter Vijay Tendulkar.
|
E145533
|
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: Akrosh | Statement: [Vijay Tendulkar, screenwriterOf, Akrosh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akrosh Context triple: [Vijay Tendulkar, screenwriterOf, Akrosh]
-
A.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
-
B.
Karmanor
Karmanor is a minor figure in Greek mythology known as a Cretan hero or priest associated with the goddess Demeter.
-
C.
Khoni
Khoni is a small town in western Georgia’s Imereti region, known for its historical churches and surrounding natural landscapes.
-
D.
Shimsha
Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
-
E.
Usakhelauri
Usakhelauri is a rare and highly prized Georgian red wine known for its natural sweetness, aromatic complexity, and limited production in the mountainous Racha region.
- 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: Akrosh Triple: [Vijay Tendulkar, screenwriterOf, Akrosh]
Generated description
Akrosh is an Indian film best known as a hard-hitting social drama written by acclaimed playwright and screenwriter Vijay Tendulkar.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Akrosh Target entity description: Akrosh is an Indian film best known as a hard-hitting social drama written by acclaimed playwright and screenwriter Vijay Tendulkar.
-
A.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
-
B.
Karmanor
Karmanor is a minor figure in Greek mythology known as a Cretan hero or priest associated with the goddess Demeter.
-
C.
Khoni
Khoni is a small town in western Georgia’s Imereti region, known for its historical churches and surrounding natural landscapes.
-
D.
Shimsha
Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
-
E.
Usakhelauri
Usakhelauri is a rare and highly prized Georgian red wine known for its natural sweetness, aromatic complexity, and limited production in the mountainous Racha region.
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7e28df08190b5be7794442a6f21 |
completed | March 1, 2026, 10:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac996dcd3481909543f1b9758a0f91 |
completed | March 7, 2026, 9:32 p.m. |
| NEDg | Description generation | batch_69ac9df823208190ae27a659ac283e2a |
completed | March 7, 2026, 9:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac9e4788d08190b2a6f34bbf9f2671 |
completed | March 7, 2026, 9:53 p.m. |
Created at: March 1, 2026, 7:41 p.m.