Triple

T5006685
Position Surface form Disambiguated ID Type / Status
Subject Lionel Pincus E112512 entity
Predicate employer P7 FINISHED
Object Warburg Pincus E490101 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: Warburg Pincus | Statement: [Lionel Pincus, employer, Warburg Pincus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warburg Pincus
Context triple: [Lionel Pincus, employer, Warburg Pincus]
  • A. Warburg Pincus chosen
    Warburg Pincus is a global private equity firm known for growth investing across a wide range of industries and regions.
  • B. Permira
    Permira is a global private equity firm that invests in and acquires businesses across sectors such as technology, consumer, healthcare, and financial services.
  • C. The Carlyle Group
    The Carlyle Group is a major global private equity and investment firm known for managing large alternative asset portfolios and employing prominent political and financial figures.
  • D. Bain Capital
    Bain Capital is a prominent private investment firm based in Boston, known for its leveraged buyouts, private equity, and alternative asset management activities worldwide.
  • E. Thoma Bravo
    Thoma Bravo is a leading private equity investment firm known for acquiring and growing software and technology companies.
  • 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_69bd4433d0b08190877e83959ef40d81 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd72e75db88190bccb30b93638a7a4 completed March 20, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69bec34a07c0819089953ebcbe9cc3ff completed March 21, 2026, 4:11 p.m.
Created at: March 20, 2026, 1:35 p.m.