Triple
T20113756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief Scientist at NIIT |
E490398
|
entity |
| Predicate | organization |
P629
|
FINISHED |
| Object | NIIT Limited |
—
|
NE NERFINISHED |
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: NIIT Limited | Statement: [Chief Scientist at NIIT, organization, NIIT Limited]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NIIT Limited Context triple: [Chief Scientist at NIIT, organization, NIIT Limited]
-
A.
NIIT
chosen
NIIT is an Indian multinational skills and talent development company best known for its IT and education training services.
-
B.
NASSCOM
NASSCOM is an Indian trade association and industry body representing the country’s information technology (IT) and business process management (BPM) sectors.
-
C.
Infosys Foundation
Infosys Foundation is the philanthropic arm of Infosys, focusing on large-scale initiatives in education, healthcare, rural development, and social welfare across India.
-
D.
EdgeVerve Systems
EdgeVerve Systems is a technology company specializing in software products and platforms, particularly in areas like banking, automation, and artificial intelligence.
-
E.
Nisum Technologies
Nisum Technologies is a global technology consulting and software development firm specializing in digital transformation, e-commerce, and enterprise solutions for large and mid-sized businesses.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666e31af081908d8e0c867c388a73 |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:29 p.m.