Triple

T4303926
Position Surface form Disambiguated ID Type / Status
Subject Charles Garnier E99906 entity
Predicate hasWorkInCity P24431 FINISHED
Object Paris E568 NE FINISHED

How this triple was built (3 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: Paris | Statement: [Charles Garnier, hasWorkInCity, Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris
Context triple: [Charles Garnier, hasWorkInCity, Paris]
  • A. Paris
    Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
  • B. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • C. Parigi
    Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
  • D. Lyon
    Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
  • E. Paris Bar
    The Paris Bar is the professional association and regulatory body for lawyers practicing in Paris, France.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasWorkInCity
Context triple: [Charles Garnier, hasWorkInCity, Paris]
  • A. hasWorksLocatedIn
    Indicates that the works or creations associated with an entity are situated or stored in a specified location.
  • B. workCity chosen
    Indicates the city in which an entity (typically a person) performs their work or job.
  • C. isInCity
    Indicates that one entity is located within the geographical boundaries of a specified city.
  • D. hasTargetCity
    Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
  • E. hasCityRole
    Indicates that an entity holds or is assigned a specific role, function, or status within a particular city.
  • F. None of above.

Provenance (4 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b350b792608190ac778b79c740256a completed March 12, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e4ebb3808190a4be632e36140648 completed March 14, 2026, 10:44 p.m.
PD Predicate disambiguation batch_69b347ff45cc8190b0cc335a94cc3d73 completed March 12, 2026, 11:10 p.m.
Created at: March 12, 2026, 11:09 p.m.