Triple
T16706197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karsanbhai Patel |
E405976
|
entity |
| Predicate | founded |
P104
|
FINISHED |
| Object | Nirma |
E1229638
|
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: Nirma | Statement: [Karsanbhai Patel, founded, Nirma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nirma Context triple: [Karsanbhai Patel, founded, Nirma]
-
A.
Nirma detergent
chosen
Nirma detergent is a popular Indian laundry detergent brand that revolutionized the country’s detergent market by offering an affordable alternative to established multinational products.
-
B.
Neutrogena
Neutrogena is a widely recognized skincare and cosmetics brand known for its dermatologist-recommended products, including facial cleansers, moisturizers, sunscreens, and acne treatments.
-
C.
HUL
HUL is the National Rail station code for Hull Paragon Interchange, the main railway and bus station in Kingston upon Hull, England.
-
D.
Lakmé
Lakmé is a French opera by Léo Delibes, best known for its exotic setting in colonial India and its famous "Flower Duet."
-
E.
Lifebuoy
Lifebuoy is a long-established global soap and hygiene brand known for its antibacterial products and health-focused marketing.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3833695908190afd4d2ece233be00 |
completed | April 18, 2026, 1:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d38a1348190bf51af9847a16aa5 |
completed | May 10, 2026, 2:59 p.m. |
Created at: April 10, 2026, 5:19 a.m.