Triple

T13933117
Position Surface form Disambiguated ID Type / Status
Subject The Keynote Speaker E335040 entity
Predicate hasPart P35 FINISHED
Object "Zilla" E16133 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: "Zilla" | Statement: [The Keynote Speaker, hasPart, "Zilla"]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: "Zilla"
Context triple: [The Keynote Speaker, hasPart, "Zilla"]
  • A. Monstruo Verde
    Monstruo Verde is the popular nickname of Honduran football club C.D. Marathón, referencing its traditional green colors and fierce competitive identity.
  • B. Kaiju chosen
    Kaiju are colossal, monstrous creatures from Japanese science fiction and popular culture, often depicted as city-destroying beasts that battle humanity or other giant monsters.
  • C. Monster Man
    Monster Man is a 2003 American horror-comedy film known for its blend of slasher elements and dark humor.
  • D. Zzzax
    Zzzax is an electricity-based Marvel supervillain composed of pure energy who frequently battles the Hulk and other heroes.
  • E. The Kaiju Preservation Society
    The Kaiju Preservation Society is a science fiction novel by John Scalzi that follows a secret organization tasked with protecting giant interdimensional monsters from both their own world and human exploitation.
  • 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_69d81c5f739081908bc05b2461f54828 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2cf28df081908d897d7b9ec7939d completed April 14, 2026, 12:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce865ab4819088221189344b3801 completed May 3, 2026, 10:39 p.m.
Created at: April 9, 2026, 10:17 p.m.