Triple

T13120244
Position Surface form Disambiguated ID Type / Status
Subject Pipe Land E311700 entity
Predicate hasEnemyType P15619 FINISHED
Object Lava Lotus
Lava Lotus is a recurring fire-based plant enemy in the Super Mario video game series that emerges from lava to shoot fireballs at the player.
 E1022819 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: Lava Lotus | Statement: [Pipe Land, hasEnemyType, Lava Lotus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lava Lotus
Context triple: [Pipe Land, hasEnemyType, Lava Lotus]
  • A. Fire Flower
    The Fire Flower is a recurring power-up in the Super Mario series that lets Mario throw fireballs to defeat enemies and interact with the environment.
  • B. Lodoselo
    Lodoselo is a small village in the municipality of Sarreaus, in the province of Ourense, Galicia, Spain.
  • C. Matareya
    Matareya is a district in northeastern Cairo, Egypt, known for its ancient Heliopolis archaeological remains and historic religious sites.
  • D. Crystal Lotus
    Crystal Lotus is an upscale Chinese restaurant at Hong Kong Disneyland Hotel known for its creative dim sum and dishes themed around Disney characters.
  • E. Sula Rasa
    Sula Rasa is a premium Indian red wine produced by Sula Vineyards, known for its rich, full-bodied character and oak-aged complexity.
  • 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: Lava Lotus
Triple: [Pipe Land, hasEnemyType, Lava Lotus]
Generated description
Lava Lotus is a recurring fire-based plant enemy in the Super Mario video game series that emerges from lava to shoot fireballs at the player.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lava Lotus
Target entity description: Lava Lotus is a recurring fire-based plant enemy in the Super Mario video game series that emerges from lava to shoot fireballs at the player.
  • A. Fire Flower
    The Fire Flower is a recurring power-up in the Super Mario series that lets Mario throw fireballs to defeat enemies and interact with the environment.
  • B. Lodoselo
    Lodoselo is a small village in the municipality of Sarreaus, in the province of Ourense, Galicia, Spain.
  • C. Matareya
    Matareya is a district in northeastern Cairo, Egypt, known for its ancient Heliopolis archaeological remains and historic religious sites.
  • D. Crystal Lotus
    Crystal Lotus is an upscale Chinese restaurant at Hong Kong Disneyland Hotel known for its creative dim sum and dishes themed around Disney characters.
  • E. Sula Rasa
    Sula Rasa is a premium Indian red wine produced by Sula Vineyards, known for its rich, full-bodied character and oak-aged complexity.
  • 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_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_69f6e286de608190bf46af2eb656bb79 completed May 3, 2026, 5:52 a.m.
NEDg Description generation batch_69f6e42cd5408190b687dfae73e2a720 completed May 3, 2026, 5:59 a.m.
NED2 Entity disambiguation (via description) batch_69f6e5293ee481908d9a90266ac5c3e6 completed May 3, 2026, 6:03 a.m.
Created at: April 9, 2026, 9:06 p.m.