Triple

T38602950
Position Surface form Disambiguated ID Type / Status
Subject One City, Nine Towns project E934264 entity
Predicate themeExample P7707 FINISHED
Object Anting New Town modeled on German style 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: Anting New Town modeled on German style | Statement: [One City, Nine Towns project, themeExample, Anting New Town modeled on German style]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: themeExample
Context triple: [One City, Nine Towns project, themeExample, Anting New Town modeled on German style]
  • A. themeExamples chosen
    Indicates that the related entity serves as an example or illustration of the theme expressed by the subject.
  • B. themeFor
    Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
  • C. theme
    Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
  • D. themeInspiration
    Indicates that one entity serves as the creative source or conceptual basis that inspires or shapes the theme expressed in another entity.
  • E. themeKey
    Indicates that one entity serves as the primary subject, topic, or thematic focus associated with another entity.
  • 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_69f76ecc17688190b389b693a5927501 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcdb0de8c08190928cd1323f80ab5c completed May 7, 2026, 6:33 p.m.
PD Predicate disambiguation batch_69fcd9017dd88190b32a73fe78909740 completed May 7, 2026, 6:25 p.m.
Created at: May 3, 2026, 4:32 p.m.