Triple

T8288804
Position Surface form Disambiguated ID Type / Status
Subject DISM E193844 entity
Predicate replaces P101 FINISHED
Object Intlcfg E625237 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: Intlcfg | Statement: [DISM, replaces, Intlcfg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Intlcfg
Context triple: [DISM, replaces, Intlcfg]
  • A. Region and Language
    Region and Language is a Windows Control Panel tool that lets users configure system locale, regional formats, and language settings.
  • B. Langues
    Langues were the regional administrative divisions of the Knights Hospitaller, grouping members by their geographic and linguistic origins.
  • C. Translations
    Translations is a critically acclaimed play by Irish dramatist Brian Friel that explores themes of language, identity, and colonialism in 19th-century rural Ireland.
  • D. Unicode CLDR
    Unicode CLDR is a standardized, collaboratively maintained repository of locale data that underpins internationalization and localization features in software and digital platforms worldwide.
  • E. Locale Data Markup Language chosen
    Locale Data Markup Language (LDML) is an XML-based standard for representing locale-specific data such as date, time, number, and language formats used in internationalization and localization.
  • 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_69ca82e32db481908b72f3804fa71152 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7c98e15c8190ac2a0b2a5ff834c9 completed March 31, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd68898610819091a76f89cd2a6aa2 completed April 1, 2026, 6:48 p.m.
Created at: March 30, 2026, 5:52 p.m.