Triple

T16921770
Position Surface form Disambiguated ID Type / Status
Subject Aeolis Mons E410458 entity
Predicate hasNamedAfterPersonVariant P107513 FINISHED
Object Mount Sharp named after Robert P. Sharp LITERAL 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: Mount Sharp named after Robert P. Sharp | Statement: [Aeolis Mons, hasNamedAfterPersonVariant, Mount Sharp named after Robert P. Sharp]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNamedAfterPersonVariant
Context triple: [Aeolis Mons, hasNamedAfterPersonVariant, Mount Sharp named after Robert P. Sharp]
  • A. hasNamedAfterPerson chosen
    Indicates that one entity is named in honor of, or derived from the name of, a specific person.
  • B. hasCharacterNamedAfter
    Indicates that one entity has a character whose name is derived from or intentionally based on another entity.
  • C. hasPrincipleNamedAfter
    Indicates that an entity has a principle, rule, or law that is named after a specified entity.
  • D. hasPartiallyNamedAfter
    Indicates that one entity is partially named in reference to another entity, such that only a portion of its name derives from or honors the other.
  • E. hasHistoricNameVariant
    Indicates that an entity has an alternative name that was used in a historical period or past context.
  • F. None of above.

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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cdef7df881908b69aa3c4f50ef94 completed April 18, 2026, 6:31 p.m.
PD Predicate disambiguation batch_69e32b982f548190b08414d55810de19 completed April 18, 2026, 6:58 a.m.
Created at: April 10, 2026, 5:30 a.m.