Triple

T3030911
Position Surface form Disambiguated ID Type / Status
Subject Steve McMichael E82891 entity
Predicate nickname P55 FINISHED
Object 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.
 E320526 NE FINISHED

How this triple was built (4 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: Mongo | Statement: [Steve McMichael, nickname, Mongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mongo
Context triple: [Steve McMichael, nickname, Mongo]
  • A. MariaDB
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • B. Mongoose
    Mongoose is a popular Node.js object data modeling (ODM) library that provides a schema-based solution for modeling and interacting with MongoDB databases.
  • C. BSON
    BSON is a binary-encoded serialization format commonly used by MongoDB to store and transfer structured data efficiently while supporting additional data types beyond those in JSON.
  • D. MySQL
    MySQL is a widely used open-source relational database management system known for its reliability, performance, and role in powering many web applications and services.
  • E. Amazon DocumentDB
    Amazon DocumentDB is a fully managed, scalable document database service from AWS designed to be compatible with MongoDB workloads and optimized for performance, durability, and security in the cloud.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mongo
Triple: [Steve McMichael, nickname, Mongo]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mongo
Target entity description: 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.
  • A. MariaDB
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • B. Mongoose
    Mongoose is a popular Node.js object data modeling (ODM) library that provides a schema-based solution for modeling and interacting with MongoDB databases.
  • C. BSON
    BSON is a binary-encoded serialization format commonly used by MongoDB to store and transfer structured data efficiently while supporting additional data types beyond those in JSON.
  • D. MySQL
    MySQL is a widely used open-source relational database management system known for its reliability, performance, and role in powering many web applications and services.
  • E. Amazon DocumentDB
    Amazon DocumentDB is a fully managed, scalable document database service from AWS designed to be compatible with MongoDB workloads and optimized for performance, durability, and security in the cloud.
  • F. None of above. chosen

Provenance (5 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_69ad8b21a62881908ec5dd4fba4a187c completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9aee2fec81908116939a8d773fc4 completed March 8, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1debd245c819081eb2dec470f9156 completed March 11, 2026, 9:29 p.m.
NEDg Description generation batch_69b1dfc77c1881909688d5037682fa01 completed March 11, 2026, 9:33 p.m.
NED2 Entity disambiguation (via description) batch_69b1e03121148190840fc48a50c4ec0e completed March 11, 2026, 9:35 p.m.
Created at: March 8, 2026, 3:01 p.m.