Triple

T13120256
Position Surface form Disambiguated ID Type / Status
Subject Pipe Land E311700 entity
Predicate hasAlternativeName P39 FINISHED
Object Pipe Maze E1022820 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: Pipe Maze | Statement: [Pipe Land, hasAlternativeName, Pipe Maze]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pipe Maze
Context triple: [Pipe Land, hasAlternativeName, Pipe Maze]
  • A. Pipe Maze chosen
    Pipe Maze is a themed world in the Super Mario series characterized by its extensive network of warp pipes and maze-like level design.
  • B. Maze
    Maze is a Slovenian surname most notably borne by Tina Maze, one of Slovenia’s greatest alpine ski racers.
  • C. Dragonfly Maze
    Dragonfly Maze is a puzzle-themed hedge maze and family-friendly attraction located in the Cotswold village of Bourton-on-the-Water in England.
  • D. the Maze
    The Maze was the informal name for Long Kesh prison in Northern Ireland, a high-security facility central to the Troubles and known for housing paramilitary prisoners and hunger strikers.
  • E. Laberintos
    Laberintos is a collection of short stories by Jorge Luis Borges that explores themes of infinity, mirrors, and labyrinthine realities through intricate, metaphysical narratives.
  • 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_69d806a9fe888190b081e2d9ea665d6c completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98196e69081909111407ee3d9f08e completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eadcd7048190aa740262679e5bab completed May 3, 2026, 6:27 a.m.
Created at: April 9, 2026, 9:06 p.m.