Triple
T22075521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahal (1949 film) |
E545511
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Vijayalaxmi
Vijayalaxmi was an Indian actress known for her role in the 1949 Hindi film "Mahal," a landmark in early Indian cinema.
|
E1518599
|
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: Vijayalaxmi | Statement: [Mahal (1949 film), starring, Vijayalaxmi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vijayalaxmi Context triple: [Mahal (1949 film), starring, Vijayalaxmi]
-
A.
Vijayashanti
Vijayashanti is an acclaimed Indian actress and politician, best known for her powerful roles in Telugu cinema and her later career as a public servant.
-
B.
Uma Maheswari
Uma Maheswari is a Hindu goddess venerated as the consort of Lord Shiva and a local deity associated with the town of Sirkazhi in Tamil Nadu, India.
-
C.
Suhasini Mulay
Suhasini Mulay is an Indian actress and documentary filmmaker known for her work in parallel cinema and acclaimed character roles in Hindi and regional films.
-
D.
Savithri
Savithri was a legendary Indian actress renowned for her powerful performances and enduring impact on Tamil and South Indian cinema.
-
E.
Leela Naidu
Leela Naidu was an Indian actress and former Miss India known for her acclaimed but selective film work, including notable roles in both Indian and international cinema.
- 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: Vijayalaxmi Triple: [Mahal (1949 film), starring, Vijayalaxmi]
Generated description
Vijayalaxmi was an Indian actress known for her role in the 1949 Hindi film "Mahal," a landmark in early Indian cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vijayalaxmi Target entity description: Vijayalaxmi was an Indian actress known for her role in the 1949 Hindi film "Mahal," a landmark in early Indian cinema.
-
A.
Vijayashanti
Vijayashanti is an acclaimed Indian actress and politician, best known for her powerful roles in Telugu cinema and her later career as a public servant.
-
B.
Uma Maheswari
Uma Maheswari is a Hindu goddess venerated as the consort of Lord Shiva and a local deity associated with the town of Sirkazhi in Tamil Nadu, India.
-
C.
Suhasini Mulay
Suhasini Mulay is an Indian actress and documentary filmmaker known for her work in parallel cinema and acclaimed character roles in Hindi and regional films.
-
D.
Savithri
Savithri was a legendary Indian actress renowned for her powerful performances and enduring impact on Tamil and South Indian cinema.
-
E.
Leela Naidu
Leela Naidu was an Indian actress and former Miss India known for her acclaimed but selective film work, including notable roles in both Indian and international cinema.
- 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b1904881909a1769ce8be39e05 |
completed | April 28, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a8793a1ec8190977047d2c094845d |
completed | May 18, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_6a0a8a706f8481908e3c09c936948576 |
completed | May 18, 2026, 3:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a8aeed53c8190a261573a43a03929 |
completed | May 18, 2026, 3:43 a.m. |
Created at: April 16, 2026, 8:28 p.m.