Triple
T21944817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hu Tu Tu |
E541907
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Panna Barve
Panna Barve is a central character in the 1999 Hindi political drama film "Hu Tu Tu," portrayed as a young woman caught in the web of corruption and power struggles.
|
E1509457
|
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: Panna Barve | Statement: [Hu Tu Tu, featuresCharacter, Panna Barve]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Panna Barve Context triple: [Hu Tu Tu, featuresCharacter, Panna Barve]
-
A.
Mukta Barve
Mukta Barve is a prominent Indian actress and producer acclaimed for her versatile performances in Marathi films, television, and theatre.
-
B.
Govindi Bai Pant
Govindi Bai Pant was the wife of Indian freedom fighter and prominent political leader Govind Ballabh Pant.
-
C.
Sondhwari Malvi
Sondhwari Malvi is a regional dialect of the Malvi language spoken in parts of central India.
-
D.
Madhu Shah
Madhu Shah is known as the wife of Indian film and television actor Satish Shah.
-
E.
Venki
Venki is the commonly used nickname of Venki Ramakrishnan, the Nobel Prize–winning structural biologist known for his work on the ribosome.
- 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: Panna Barve Triple: [Hu Tu Tu, featuresCharacter, Panna Barve]
Generated description
Panna Barve is a central character in the 1999 Hindi political drama film "Hu Tu Tu," portrayed as a young woman caught in the web of corruption and power struggles.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Panna Barve Target entity description: Panna Barve is a central character in the 1999 Hindi political drama film "Hu Tu Tu," portrayed as a young woman caught in the web of corruption and power struggles.
-
A.
Mukta Barve
Mukta Barve is a prominent Indian actress and producer acclaimed for her versatile performances in Marathi films, television, and theatre.
-
B.
Govindi Bai Pant
Govindi Bai Pant was the wife of Indian freedom fighter and prominent political leader Govind Ballabh Pant.
-
C.
Sondhwari Malvi
Sondhwari Malvi is a regional dialect of the Malvi language spoken in parts of central India.
-
D.
Madhu Shah
Madhu Shah is known as the wife of Indian film and television actor Satish Shah.
-
E.
Venki
Venki is the commonly used nickname of Venki Ramakrishnan, the Nobel Prize–winning structural biologist known for his work on the ribosome.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242688988190a7b8f033c49368de |
completed | April 28, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a60f1f49c81909f6c17dad3bd0219 |
completed | May 18, 2026, 12:44 a.m. |
| NEDg | Description generation | batch_6a0a6200fb1c81909a4ab05fd368dafc |
completed | May 18, 2026, 12:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a626731d8819097b209ae1375ae25 |
completed | May 18, 2026, 12:50 a.m. |
Created at: April 16, 2026, 7:56 p.m.