Triple

T16865996
Position Surface form Disambiguated ID Type / Status
Subject planet Mongo E410037 entity
Predicate hasRegion P285 FINISHED
Object Arboria
Arboria is a lush, forested kingdom on the planet Mongo in the Flash Gordon universe, ruled by Prince Barin and known for its treetop cities and dangerous wildlife.
 E1237832 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: Arboria | Statement: [planet Mongo, hasRegion, Arboria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Arboria
Context triple: [planet Mongo, hasRegion, Arboria]
  • A. Cayor
    Cayor was a precolonial Wolof kingdom in what is now Senegal, emerging as a major regional power after the decline of the Wolof Empire.
  • B. Landana
    Landana is a coastal town in Angola’s Cabinda exclave, historically known as a regional trading and missionary center.
  • C. Isola
    Isola is a small alpine commune in southeastern France known for its ski resort Isola 2000 and proximity to the Italian border.
  • D. Isola
    Isola is a small island located within Lake Sils in the Upper Engadine region of the Swiss Alps.
  • E. Mahorais
    Mahorais is a French-based creole language spoken primarily on the island of Mayotte in the Indian Ocean.
  • 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: Arboria
Triple: [planet Mongo, hasRegion, Arboria]
Generated description
Arboria is a lush, forested kingdom on the planet Mongo in the Flash Gordon universe, ruled by Prince Barin and known for its treetop cities and dangerous wildlife.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Arboria
Target entity description: Arboria is a lush, forested kingdom on the planet Mongo in the Flash Gordon universe, ruled by Prince Barin and known for its treetop cities and dangerous wildlife.
  • A. Cayor
    Cayor was a precolonial Wolof kingdom in what is now Senegal, emerging as a major regional power after the decline of the Wolof Empire.
  • B. Landana
    Landana is a coastal town in Angola’s Cabinda exclave, historically known as a regional trading and missionary center.
  • C. Isola
    Isola is a small alpine commune in southeastern France known for its ski resort Isola 2000 and proximity to the Italian border.
  • D. Isola
    Isola is a small island located within Lake Sils in the Upper Engadine region of the Swiss Alps.
  • E. Mahorais
    Mahorais is a French-based creole language spoken primarily on the island of Mayotte in the Indian Ocean.
  • 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.