Triple

T15108374
Position Surface form Disambiguated ID Type / Status
Subject 10gen E360846 entity
Predicate successor P78 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: [10gen, successor, MongoDB Inc.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MongoDB Inc.
Context triple: [10gen, successor, 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. MariaDB Corporation
    MariaDB Corporation is a software company that develops and supports the MariaDB open-source relational database, a popular alternative to MySQL for enterprise and cloud applications.
  • D. 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.
  • E. Azul Systems
    Azul Systems is a software company specializing in high-performance, scalable Java runtimes and JVM technologies for enterprise applications.
  • 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_69d85a0491ec8190830960be8fafb994 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0058af8988190977d998f85893836 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69feb7e912ac8190bd0e0c9cdbbd0194 completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 3:05 a.m.