Triple

T28449052
Position Surface form Disambiguated ID Type / Status
Subject Direction générale de la sécurité extérieure E716522 entity
Predicate headquartersLocation P62 FINISHED
Object Boulevard Mortier, Paris
Boulevard Mortier, Paris is a street in the 20th arrondissement best known for hosting the main headquarters of France’s foreign intelligence service.
E1860085 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: Boulevard Mortier, Paris | Statement: [Direction générale de la sécurité extérieure, headquartersLocation, Boulevard Mortier, Paris]
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: Boulevard Mortier, Paris
Triple: [Direction générale de la sécurité extérieure, headquartersLocation, Boulevard Mortier, Paris]
Generated description
Boulevard Mortier, Paris is a street in the 20th arrondissement best known for hosting the main headquarters of France’s foreign intelligence service.

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_69efd6b76f8c8190a7ba908aca280942 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f64e70e04c819090dd3e66f7f13ca0 completed May 2, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2588fab4a481909faba4d2dfaf1cff completed June 7, 2026, 3:06 p.m.
NEDg Description generation batch_6a258d4474448190844fdc2216ecbd29 completed June 7, 2026, 3:24 p.m.
NED2 Entity disambiguation (via description) batch_6a25985cf75081909194c11833399d37 completed June 7, 2026, 4:12 p.m.
Created at: April 28, 2026, 1:50 a.m.