Triple
T4514336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanjay Gandhi |
E102118
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Maneka Gandhi |
E204524
|
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: Maneka Gandhi | Statement: [Sanjay Gandhi, spouse, Maneka Gandhi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maneka Gandhi Context triple: [Sanjay Gandhi, spouse, Maneka Gandhi]
-
A.
Maneka Gandhi
chosen
Maneka Gandhi is an Indian politician, animal rights activist, and longtime member of parliament known for her work on environmental and animal welfare issues.
-
B.
Meena Khadikar
Meena Khadikar is an Indian playback singer and composer, known for her work in Marathi and Hindi music and as a member of the renowned Mangeshkar musical family.
-
C.
Anu Khosla
Anu Khosla is one of the children of Indian-American billionaire venture capitalist and Sun Microsystems co-founder Vinod Khosla.
-
D.
Indira Varma
Indira Varma is a British actress known for her versatile roles in television, film, and theatre, including prominent performances in series such as "Game of Thrones" and "Luther."
-
E.
Neeru Khosla
Neeru Khosla is an Indian-American education advocate and co-founder of the nonprofit digital learning platform CK-12 Foundation.
- 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_69bd43d6251c81909deecce3e6e9d69c |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd572402f481908151f7899bc96306 |
completed | March 20, 2026, 2:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bda42bd41c8190a9a25ccea6947089 |
completed | March 20, 2026, 7:46 p.m. |
Created at: March 20, 2026, 1:02 p.m.