Triple

T21278478
Position Surface form Disambiguated ID Type / Status
Subject Faubourg Saint-Marcel E524452 entity
Predicate integratedInto P77 FINISHED
Object city of Paris — NE NERFINISHED

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: city of Paris | Statement: [Faubourg Saint-Marcel, integratedInto, city of Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: city of Paris
Context triple: [Faubourg Saint-Marcel, integratedInto, city of Paris]
  • A. Ville de Paris
    Ville de Paris is the municipal government and administrative authority responsible for managing and providing public services in the city of Paris, France.
  • B. Ville de Paris
    Ville de Paris was a prominent French ship of the line, originally the flagship of Admiral de Grasse, that played a central role in major naval engagements during the American Revolutionary War.
  • C. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • D. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • E. Paris
    Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b516293c819089458ea2ec85f85e completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73658f598819098a1192abfa40a12 completed April 21, 2026, 8:33 a.m.
Created at: April 16, 2026, 4:02 p.m.