Triple
T9972098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swarup Rani Nehru |
E196231
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Krishna Hutheesing |
E111172
|
NE FINISHED |
How this triple was built (2 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: Krishna Hutheesing | Statement: [Swarup Rani Nehru, child, Krishna Hutheesing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krishna Hutheesing Context triple: [Swarup Rani Nehru, child, Krishna Hutheesing]
-
A.
Krishna Hutheesing
chosen
Krishna Hutheesing was an Indian writer and member of the prominent Nehru family, known for her memoirs and biographical works about her relatives and the Indian independence movement.
-
B.
Nelson Dilipkumar
Nelson Dilipkumar is an Indian film director and screenwriter known for his darkly comic Tamil-language films and collaborations with major South Indian stars.
-
C.
Sanjiv Banga
Sanjiv Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
-
D.
Asheem Chandna
Asheem Chandna is a prominent venture capitalist known for investing in and advising leading enterprise technology and cybersecurity startups.
-
E.
Prasanna Puwanarajah
Prasanna Puwanarajah is a British actor, director, and former NHS doctor known for his work in television, film, and theatre.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb7bb03688190a3f4fc1988b8fafa |
completed | April 2, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23dd3e47c819095fef68b9939ec19 |
completed | April 5, 2026, 10:47 a.m. |
Created at: March 30, 2026, 8:48 p.m.