Triple

T31081663
Position Surface form Disambiguated ID Type / Status
Subject Rue Marcadet E792110 entity
Predicate locatedInNeighborhood P40 FINISHED
Object Grandes-Carrières neighborhood
The Grandes-Carrières neighborhood is a residential district in Paris’s 18th arrondissement, historically shaped by former gypsum quarries and now known for its mix of traditional Parisian streets and local commerce.
 E1944037 NE 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: Grandes-Carrières neighborhood | Statement: [Rue Marcadet, locatedInNeighborhood, Grandes-Carrières neighborhood]
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: Grandes-Carrières neighborhood
Triple: [Rue Marcadet, locatedInNeighborhood, Grandes-Carrières neighborhood]
Generated description
The Grandes-Carrières neighborhood is a residential district in Paris’s 18th arrondissement, historically shaped by former gypsum quarries and now known for its mix of traditional Parisian streets and local commerce.

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_69f224ce48348190bd0fc23f656ed683 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f695f9fe7c819084322bf6cdc70a13 completed May 3, 2026, 12:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292b291c6c8190bb5181ac803a6ac4 completed June 10, 2026, 9:15 a.m.
NEDg Description generation batch_6a292b93d7988190b1fe79f38def8b5f completed June 10, 2026, 9:17 a.m.
NED2 Entity disambiguation (via description) batch_6a292caa0590819087d6b9d576701697 completed June 10, 2026, 9:21 a.m.
Created at: April 29, 2026, 9:02 p.m.