Triple

T16865768
Position Surface form Disambiguated ID Type / Status
Subject Ming the Merciless E410032 entity
Predicate homePlanet P16439 FINISHED
Object Mongo
Mongo is the fictional alien planet ruled by the villainous Ming the Merciless in the Flash Gordon universe.
 E1237831 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: [Ming the Merciless, homePlanet, Mongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mongo
Context triple: [Ming the Merciless, homePlanet, Mongo]
  • 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. Mongo
    Mongo is the first child of Claireece "Precious" Jones in the novel and film "Precious," born with severe disabilities as a result of incestuous abuse.
  • C. Mongo
    Mongo is a major Bantu language spoken primarily in the Democratic Republic of the Congo by the Mongo people.
  • D. Mongo
    Mongo is the dim-witted but immensely strong henchman from the satirical Western comedy film "Blazing Saddles."
  • E. MongoDB database
    MongoDB database is a popular open-source NoSQL document-oriented database designed for scalability, flexibility, and high performance in modern applications.
  • 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: [Ming the Merciless, homePlanet, Mongo]
Generated description
Mongo is the fictional alien planet ruled by the villainous Ming the Merciless in the Flash Gordon universe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mongo
Target entity description: Mongo is the fictional alien planet ruled by the villainous Ming the Merciless in the Flash Gordon universe.
  • 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. Mongo
    Mongo is the first child of Claireece "Precious" Jones in the novel and film "Precious," born with severe disabilities as a result of incestuous abuse.
  • C. Mongo
    Mongo is a major Bantu language spoken primarily in the Democratic Republic of the Congo by the Mongo people.
  • D. Mongo
    Mongo is the dim-witted but immensely strong henchman from the satirical Western comedy film "Blazing Saddles."
  • E. MongoDB database
    MongoDB database is a popular open-source NoSQL document-oriented database designed for scalability, flexibility, and high performance in modern applications.
  • 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b5088f208190abfe937633ebe3fe completed April 18, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2a929b081909d3a5a680ae93a78 completed May 10, 2026, 5:38 p.m.
NEDg Description generation batch_6a00c355f4108190a4209599bf5f50da completed May 10, 2026, 5:41 p.m.
NED2 Entity disambiguation (via description) batch_6a00c413314881909e308588af09ce2a completed May 10, 2026, 5:44 p.m.
Created at: April 10, 2026, 5:24 a.m.