Triple

T2991
Position Surface form Disambiguated ID Type / Status
Subject Las Campanas Observatory E55 entity
Predicate languageOfOfficialName P15 FINISHED
Object Spanish 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: Spanish | Statement: [Las Campanas Observatory, languageOfOfficialName, Spanish]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageOfOfficialName
Context triple: [Las Campanas Observatory, languageOfOfficialName, Spanish]
  • A. officialLanguage
    Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
  • B. languageOfWorkOrName chosen
    Indicates the language in which a work is created or a name is expressed.
  • C. nativeLanguage
    Indicates the language that a person or entity originally learned and uses as their primary or first language.
  • D. hasOfficialLanguagePolicy
    Indicates that there exists a formally adopted rule or set of rules governing the use, status, or regulation of one or more languages within a given context or jurisdiction.
  • E. deFactoLanguage
    Indicates that a language is used in practice as the primary or common language in a context, even if it has no official legal status there.
  • 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_69a2328f0e848190ac2840eaf2d5ebd2 completed Feb. 28, 2026, 12:10 a.m.
NER Named-entity recognition batch_69a2346846608190b6b40d31f1dbd685 completed Feb. 28, 2026, 12:18 a.m.
PD Predicate disambiguation batch_69a233c396ec8190986608d07fb251d4 completed Feb. 28, 2026, 12:16 a.m.
Created at: Feb. 28, 2026, 12:13 a.m.