Triple
T20083955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thapar |
E500073
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object |
Amrita Thapar
Amrita Thapar is an Indian model and beauty pageant titleholder best known for winning the Femina Miss India Universe crown in 2005.
|
E1426053
|
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: Amrita Thapar | Statement: [Thapar, usedBy, Amrita Thapar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amrita Thapar Context triple: [Thapar, usedBy, Amrita Thapar]
-
A.
Amulya Kumar Thapar
Amulya Kumar Thapar is an individual associated with the name or work of Thapar, likely within an academic, professional, or familial context.
-
B.
B. K. Thapar
B. K. Thapar was an Indian archaeologist noted for his significant contributions to the study of the Indus Valley Civilization and other ancient South Asian cultures.
-
C.
Valmik Thapar
Valmik Thapar is an Indian conservationist, author, and wildlife expert best known for his extensive work on tiger conservation and natural history in India.
-
D.
Ritu Thapar
Ritu Thapar is an individual associated with the Thapar name, likely connected to the prominent Indian Thapar family or its institutions.
-
E.
Karan Thapar
Karan Thapar is a prominent Indian journalist and television interviewer known for his incisive and often hard-hitting political interviews.
- 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: Amrita Thapar Triple: [Thapar, usedBy, Amrita Thapar]
Generated description
Amrita Thapar is an Indian model and beauty pageant titleholder best known for winning the Femina Miss India Universe crown in 2005.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Amrita Thapar Target entity description: Amrita Thapar is an Indian model and beauty pageant titleholder best known for winning the Femina Miss India Universe crown in 2005.
-
A.
Amulya Kumar Thapar
Amulya Kumar Thapar is an individual associated with the name or work of Thapar, likely within an academic, professional, or familial context.
-
B.
B. K. Thapar
B. K. Thapar was an Indian archaeologist noted for his significant contributions to the study of the Indus Valley Civilization and other ancient South Asian cultures.
-
C.
Valmik Thapar
Valmik Thapar is an Indian conservationist, author, and wildlife expert best known for his extensive work on tiger conservation and natural history in India.
-
D.
Ritu Thapar
Ritu Thapar is an individual associated with the Thapar name, likely connected to the prominent Indian Thapar family or its institutions.
-
E.
Karan Thapar
Karan Thapar is a prominent Indian journalist and television interviewer known for his incisive and often hard-hitting political interviews.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655a2d2c81908a6b8fd2f209a825 |
completed | April 20, 2026, 5:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08706cb7bc8190b25e3ea8a9974e1f |
completed | May 16, 2026, 1:26 p.m. |
| NEDg | Description generation | batch_6a08714afbe0819086dff0c44bff04f3 |
completed | May 16, 2026, 1:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0871c291f081908678ad866cee22b1 |
completed | May 16, 2026, 1:31 p.m. |
Created at: April 11, 2026, 3:41 p.m.