Triple

T5392367
Position Surface form Disambiguated ID Type / Status
Subject Curteis E120361 entity
Predicate hasOriginalMeaningContext P21977 FINISHED
Object personal description 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: personal description | Statement: [Curteis, hasOriginalMeaningContext, personal description]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOriginalMeaningContext
Context triple: [Curteis, hasOriginalMeaningContext, personal description]
  • A. originalMeaning
    Indicates that something retains or conveys its initial, intended sense or significance, as opposed to a later or altered interpretation.
  • B. originalLanguageContext chosen
    Indicates the language in which something was first created or expressed, providing the original linguistic context for its content or meaning.
  • C. hasLiteralMeaning
    Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
  • D. hasMeaningViaJohn
    Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
  • E. originallyHad
    Indicates that an entity previously possessed, contained, or was associated with something before a change, loss, or transformation occurred.
  • 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_69bd46354c648190a38b26f107010a96 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd8719ff04819089e3a90f90b5e3fc completed March 20, 2026, 5:42 p.m.
PD Predicate disambiguation batch_69bd8463a9c88190bd760378f3026180 completed March 20, 2026, 5:31 p.m.
Created at: March 20, 2026, 2:04 p.m.