Triple

T5895187
Position Surface form Disambiguated ID Type / Status
Subject FeathersJS E131083 entity
Predicate supportsDatabase P11254 FINISHED
Object MongoDB E360848 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 | Statement: [FeathersJS, supportsDatabase, MongoDB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MongoDB
Context triple: [FeathersJS, supportsDatabase, MongoDB]
  • A. Mongo
    Mongo is the nickname of Steve "Mongo" McMichael, a former NFL defensive tackle and professional wrestler best known for his time with the Chicago Bears and WCW.
  • B. MongoDB database chosen
    MongoDB database is a popular open-source NoSQL document-oriented database designed for scalability, flexibility, and high performance in modern applications.
  • C. MongoDB Cloud
    MongoDB Cloud is a fully managed cloud database platform that provides scalable, secure, and globally distributed MongoDB database services along with tools for data management, monitoring, and analytics.
  • D. 10gen
    10gen is the original company behind the development of the MongoDB NoSQL database, later renamed MongoDB Inc.
  • E. MongoDB Inc.
    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.
  • 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_69c00857439c819095950754176aa58a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c036f3364c81909353f62ca483f24f completed March 22, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c000dfb481908cf37e5c143f4cae completed March 23, 2026, 4:22 a.m.
Created at: March 22, 2026, 3:58 p.m.