Triple
T14847336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Banerjee |
E349131
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Maya Banerjee
Maya Banerjee is known as the wife of Indian actor Victor Banerjee.
|
E1124502
|
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: Maya Banerjee | Statement: [Victor Banerjee, spouse, Maya Banerjee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maya Banerjee Context triple: [Victor Banerjee, spouse, Maya Banerjee]
-
A.
Kanika Banerjee
Kanika Banerjee was a renowned Indian Rabindra Sangeet vocalist celebrated for her emotive interpretations of Rabindranath Tagore’s songs.
-
B.
Sitara Ghattamaneni
Sitara Ghattamaneni is the daughter of Telugu film star Mahesh Babu and has gained public attention in India as a popular star kid and social media personality.
-
C.
Sukanya Rajan
Sukanya Rajan is the widow of legendary Indian sitar virtuoso Ravi Shankar and the mother of musician Anoushka Shankar.
-
D.
Janina Gavankar
Janina Gavankar is an American actress and musician known for her roles in television series such as "The L Word," "True Blood," and "The Morning Show," as well as for her work in video games and independent music.
-
E.
Annet Mahendru
Annet Mahendru is an American actress best known for her acclaimed role as Nina Sergeevna Krilova on the television series "The Americans."
- 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: Maya Banerjee Triple: [Victor Banerjee, spouse, Maya Banerjee]
Generated description
Maya Banerjee is known as the wife of Indian actor Victor Banerjee.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maya Banerjee Target entity description: Maya Banerjee is known as the wife of Indian actor Victor Banerjee.
-
A.
Kanika Banerjee
Kanika Banerjee was a renowned Indian Rabindra Sangeet vocalist celebrated for her emotive interpretations of Rabindranath Tagore’s songs.
-
B.
Sitara Ghattamaneni
Sitara Ghattamaneni is the daughter of Telugu film star Mahesh Babu and has gained public attention in India as a popular star kid and social media personality.
-
C.
Sukanya Rajan
Sukanya Rajan is the widow of legendary Indian sitar virtuoso Ravi Shankar and the mother of musician Anoushka Shankar.
-
D.
Janina Gavankar
Janina Gavankar is an American actress and musician known for her roles in television series such as "The L Word," "True Blood," and "The Morning Show," as well as for her work in video games and independent music.
-
E.
Annet Mahendru
Annet Mahendru is an American actress best known for her acclaimed role as Nina Sergeevna Krilova on the television series "The Americans."
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded29236dc8190b7d3a37d09f9fb21 |
completed | April 14, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6502d3f081909ff6fa8722769e2e |
completed | May 8, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_69fe662fa374819083367ba7f9da2272 |
completed | May 8, 2026, 10:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe67664044819084196e3e6e365415 |
completed | May 8, 2026, 10:44 p.m. |
Created at: April 10, 2026, 1:53 a.m.