Triple
T5812352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert F. Smith |
E128898
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Vista Equity Partners |
E548069
|
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: Vista Equity Partners | Statement: [Robert F. Smith, employer, Vista Equity Partners]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vista Equity Partners Context triple: [Robert F. Smith, employer, Vista Equity Partners]
-
A.
Vista Equity Partners
chosen
Vista Equity Partners is a leading American private equity firm specializing in software, data, and technology-enabled businesses.
-
B.
Veritas Capital
Veritas Capital is a private equity firm that specializes in investing in technology and government-related companies, particularly in sectors like healthcare, defense, and education.
-
C.
NextEquity Partners
NextEquity Partners is a venture capital and private equity firm known for investing in growth-stage technology and innovation-driven companies.
-
D.
Thoma Bravo
Thoma Bravo is a leading private equity investment firm known for acquiring and growing software and technology companies.
-
E.
Warburg Pincus
Warburg Pincus is a global private equity firm known for growth investing across a wide range of industries and regions.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b54c2848190bb85212689d0b511 |
completed | March 22, 2026, 5:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1826cc081909572d9bf99d5f670 |
completed | March 23, 2026, 2:12 a.m. |
Created at: March 22, 2026, 3:52 p.m.