Triple

T10047120
Position Surface form Disambiguated ID Type / Status
Subject Saint-Michel (Paris Métro) E207643 entity
Predicate locatedIn P40 FINISHED
Object Saint-Michel–Notre-Dame area
The Saint-Michel–Notre-Dame area is a central Parisian district around the Seine near Île de la Cité, known for its major transport hubs, historic architecture, and proximity to landmarks like Notre-Dame Cathedral and the Latin Quarter.
E837676 NE FINISHED

How this triple was built (4 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: Saint-Michel–Notre-Dame area | Statement: [Saint-Michel (Paris Métro), locatedIn, Saint-Michel–Notre-Dame area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saint-Michel–Notre-Dame area
Context triple: [Saint-Michel (Paris Métro), locatedIn, Saint-Michel–Notre-Dame area]
  • A. Downtown Paris Historic District
    Downtown Paris Historic District is a preserved central business and residential area in Paris, Kentucky, noted for its concentration of historic architecture and its role in the town’s commercial and civic life.
  • B. Quartier Part-Dieu
    Quartier Part-Dieu is Lyon’s main business district, known for its high-rise offices, major shopping center, and one of France’s busiest railway stations.
  • C. Gros-Caillou quarter
    The Gros-Caillou quarter is a central Parisian neighborhood in the 7th arrondissement, known for its elegant residential streets, proximity to the Eiffel Tower, and numerous embassies and cultural institutions.
  • D. quartier Saint-Merri
    Quartier Saint-Merri is a historic central Paris neighborhood in the 4th arrondissement, known for its medieval streets, proximity to the Centre Pompidou, and vibrant cultural life.
  • E. Marais district
    The Marais district is a historic central Paris neighborhood known for its preserved medieval streets, trendy boutiques, vibrant LGBTQ+ scene, and major cultural sites like the Musée Picasso and the Place des Vosges.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Saint-Michel–Notre-Dame area
Triple: [Saint-Michel (Paris Métro), locatedIn, Saint-Michel–Notre-Dame area]
Generated description
The Saint-Michel–Notre-Dame area is a central Parisian district around the Seine near Île de la Cité, known for its major transport hubs, historic architecture, and proximity to landmarks like Notre-Dame Cathedral and the Latin Quarter.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Saint-Michel–Notre-Dame area
Target entity description: The Saint-Michel–Notre-Dame area is a central Parisian district around the Seine near Île de la Cité, known for its major transport hubs, historic architecture, and proximity to landmarks like Notre-Dame Cathedral and the Latin Quarter.
  • A. Downtown Paris Historic District
    Downtown Paris Historic District is a preserved central business and residential area in Paris, Kentucky, noted for its concentration of historic architecture and its role in the town’s commercial and civic life.
  • B. Quartier Part-Dieu
    Quartier Part-Dieu is Lyon’s main business district, known for its high-rise offices, major shopping center, and one of France’s busiest railway stations.
  • C. Gros-Caillou quarter
    The Gros-Caillou quarter is a central Parisian neighborhood in the 7th arrondissement, known for its elegant residential streets, proximity to the Eiffel Tower, and numerous embassies and cultural institutions.
  • D. quartier Saint-Merri
    Quartier Saint-Merri is a historic central Paris neighborhood in the 4th arrondissement, known for its medieval streets, proximity to the Centre Pompidou, and vibrant cultural life.
  • E. Marais district
    The Marais district is a historic central Paris neighborhood known for its preserved medieval streets, trendy boutiques, vibrant LGBTQ+ scene, and major cultural sites like the Musée Picasso and the Place des Vosges.
  • F. None of above. chosen

Provenance (5 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_69ca835ad0608190b7c80b292da004f5 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf664dd881908786fcd802bf10da completed April 2, 2026, 2:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d282888bac81909ccb5db5724c416d completed April 5, 2026, 3:40 p.m.
NEDg Description generation batch_69d28391f8fc8190964cdccaf5625617 completed April 5, 2026, 3:45 p.m.
NED2 Entity disambiguation (via description) batch_69d284604dc88190b452ee847d3390dd completed April 5, 2026, 3:48 p.m.
Created at: March 30, 2026, 8:56 p.m.