Triple

T3460423
Position Surface form Disambiguated ID Type / Status
Subject We Can Be Heroes E73009 entity
Predicate featuresCharacter P626 FINISHED
Object Lavagirl E358584 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: Lavagirl | Statement: [We Can Be Heroes, featuresCharacter, Lavagirl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lavagirl
Context triple: [We Can Be Heroes, featuresCharacter, Lavagirl]
  • A. Lavagirl chosen
    Lavagirl is a fiery superheroine from the family adventure film "The Adventures of Sharkboy and Lavagirl in 3-D," known for her lava-based powers and partnership with Sharkboy in a dreamlike fantasy world.
  • B. Lela
    Lela is a feminine given name used in various cultures, often as a variant of Leila or Layla.
  • C. Chava
    Chava is the Hebrew form of the name Eve, traditionally associated with the first woman in the Biblical creation narrative.
  • D. Lilia
    Lilia is a feminine given name, often considered a variant of Lily and associated with the elegance and symbolism of the lily flower.
  • E. Daria
    Daria is an animated television series centered on the intelligent, sarcastic teenager Daria Morgendorffer as she navigates high school life with deadpan wit and social commentary.
  • 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_69ad85b224d481908ff8be51338d24ff completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbae5ff848190880fa416a123bc4a completed March 8, 2026, 6:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3680170e081909c0d3a39a741280d completed March 13, 2026, 1:27 a.m.
Created at: March 8, 2026, 3:17 p.m.