Triple

T26284078
Position Surface form Disambiguated ID Type / Status
Subject Super Mario Land 2: 6 Golden Coins E661082 entity
Predicate zone P2160 FINISHED
Object Mario Zone
Mario Zone is a toy-themed world shaped like Mario himself that serves as one of the main platforming areas in the Game Boy title Super Mario Land 2: 6 Golden Coins.
E1719032 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: Mario Zone | Statement: [Super Mario Land 2: 6 Golden Coins, zone, Mario Zone]
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: Mario Zone
Triple: [Super Mario Land 2: 6 Golden Coins, zone, Mario Zone]
Generated description
Mario Zone is a toy-themed world shaped like Mario himself that serves as one of the main platforming areas in the Game Boy title Super Mario Land 2: 6 Golden Coins.

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_69ee812bbd448190be4d7478b057990a completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60e76a034819088e757b72d480585 completed May 2, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118fbff9c881909a342fd394293b91 completed May 23, 2026, 11:30 a.m.
NEDg Description generation batch_6a1190549934819082b10e07b035a7b9 completed May 23, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_6a11928405ac81908559a169b90f04a8 completed May 23, 2026, 11:41 a.m.
Created at: April 26, 2026, 10:03 p.m.