Triple
T5542579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N. R. Narayana Murthy |
E145325
|
entity |
| Predicate | founded |
P104
|
FINISHED |
| Object | Infosys |
E64550
|
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: Infosys | Statement: [N. R. Narayana Murthy, founded, Infosys]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Infosys Context triple: [N. R. Narayana Murthy, founded, Infosys]
-
A.
Infosys
chosen
Infosys is a leading Indian multinational IT services and consulting company known for its global technology solutions and innovation initiatives.
-
B.
Wipro Limited
Wipro Limited is a major Indian multinational information technology, consulting, and business process services company headquartered in Bengaluru.
-
C.
Tata Consultancy Services
Tata Consultancy Services is a leading global IT services, consulting, and business solutions company headquartered in India and part of the Tata Group conglomerate.
-
D.
HCL Technologies
HCL Technologies is a global Indian IT services and consulting company known for providing software development, infrastructure management, and digital transformation solutions to enterprises worldwide.
-
E.
Capgemini
Capgemini is a global consulting, technology services, and digital transformation company headquartered in France.
- 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_69c008fa64888190adae56c8f9ea4031 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fc7e26481908cec8d0483170ea5 |
completed | March 22, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04cec35248190bae940a95e79a586 |
completed | March 22, 2026, 8:11 p.m. |
Created at: March 22, 2026, 3:35 p.m.