Triple

T3482227
Position Surface form Disambiguated ID Type / Status
Subject Dwight Merriman E73517 entity
Predicate employer P7 FINISHED
Object MongoDB Inc. E360845 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: MongoDB Inc. | Statement: [Dwight Merriman, employer, MongoDB Inc.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MongoDB Inc.
Context triple: [Dwight Merriman, employer, MongoDB Inc.]
  • A. MongoDB Inc. chosen
    MongoDB Inc. is a software company best known for developing the popular open-source NoSQL document database MongoDB, widely used for scalable, modern application development.
  • B. 10gen
    10gen is the original company behind the development of the MongoDB NoSQL database, later renamed MongoDB Inc.
  • C. Palantir Technologies
    Palantir Technologies is an American software company specializing in big data analytics platforms used by governments and large enterprises for intelligence, security, and operational decision-making.
  • D. Azul Systems
    Azul Systems is a software company specializing in high-performance, scalable Java runtimes and JVM technologies for enterprise applications.
  • E. Relational Technology Inc.
    Relational Technology Inc. was a pioneering software company best known for developing and marketing the INGRES relational database system, one of the early commercial SQL-based databases.
  • 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_69ad85b3c9b08190857cae74c7f36da9 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb76b5188190bf8f8a3f646a7184 completed March 8, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e5efe9c819087fbda6832598c04 completed March 13, 2026, 3:02 a.m.
Created at: March 8, 2026, 3:17 p.m.