Triple

T21422723
Position Surface form Disambiguated ID Type / Status
Subject Nona E528475 entity
Predicate hasCompanion P22642 FINISHED
Object Morta NE NERFINISHED

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: Morta | Statement: [Nona, hasCompanion, Morta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Morta
Context triple: [Nona, hasCompanion, Morta]
  • A. Morta chosen
    Morta is the Roman goddess of death and destiny, one of the three Fates who determines the moment of each mortal’s death by cutting the thread of life.
  • B. Mortus
    Mortus is the main villain of the 1995 Sega Genesis beat ’em up game Comix Zone, a demonic comic-book creator who brings his own drawings to life to battle the hero.
  • C. Malemort
    Malemort is a commune in the Corrèze department of south-central France, situated near the town of Brive-la-Gaillarde.
  • D. Toten
    Toten is a traditional rural district in eastern Norway known for its agriculture and scenic landscape, located within Innlandet county.
  • E. Mort
    Mort is a comic fantasy novel in Terry Pratchett’s Discworld series that follows a young apprentice to Death himself.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c455f3688190810bc96365791b0f completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee8139ce848190b812d6d07f1bdef8 completed April 26, 2026, 9:18 p.m.
Created at: April 16, 2026, 5:48 p.m.