Triple
T15231571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Kakkar |
E364014
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Kakkar
Kakkar is an Indian-origin surname commonly borne by individuals and families from the Indian subcontinent.
|
E1144400
|
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: Kakkar | Statement: [Lord Kakkar, familyName, Kakkar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kakkar Context triple: [Lord Kakkar, familyName, Kakkar]
-
A.
Gaghan
Gaghan is the surname of Stephen Gaghan, an American screenwriter and director known for works like "Traffic" and "Syriana."
-
B.
Shekhar
Shekhar is an Indian filmmaker and actor best known for directing acclaimed films such as "Bandit Queen" and the historical drama "Elizabeth."
-
C.
Karamlesh
Karamlesh is a historic Assyrian Christian town in northern Iraq’s Nineveh Plains, known for its ancient churches and proximity to Mosul.
-
D.
Kulluka Bhatta
Kulluka Bhatta was a prominent medieval Indian scholar best known for his influential Sanskrit commentary on the Hindu legal text Manusmriti.
-
E.
Yashpal
Yashpal was an Indian revolutionary and later a noted Hindi writer known for his socialist views and politically charged novels.
- 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: Kakkar Triple: [Lord Kakkar, familyName, Kakkar]
Generated description
Kakkar is an Indian-origin surname commonly borne by individuals and families from the Indian subcontinent.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kakkar Target entity description: Kakkar is an Indian-origin surname commonly borne by individuals and families from the Indian subcontinent.
-
A.
Gaghan
Gaghan is the surname of Stephen Gaghan, an American screenwriter and director known for works like "Traffic" and "Syriana."
-
B.
Shekhar
Shekhar is an Indian filmmaker and actor best known for directing acclaimed films such as "Bandit Queen" and the historical drama "Elizabeth."
-
C.
Karamlesh
Karamlesh is a historic Assyrian Christian town in northern Iraq’s Nineveh Plains, known for its ancient churches and proximity to Mosul.
-
D.
Kulluka Bhatta
Kulluka Bhatta was a prominent medieval Indian scholar best known for his influential Sanskrit commentary on the Hindu legal text Manusmriti.
-
E.
Yashpal
Yashpal was an Indian revolutionary and later a noted Hindi writer known for his socialist views and politically charged novels.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078e27408190bc13c0ca441f5594 |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd3beae88190a91af2c9a7def8f8 |
completed | May 9, 2026, 7:07 a.m. |
| NEDg | Description generation | batch_69fede3ef86481908b21bb8c43e490a0 |
completed | May 9, 2026, 7:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fedec501408190831c1cfa38c0db15 |
completed | May 9, 2026, 7:14 a.m. |
Created at: April 10, 2026, 3:12 a.m.