Triple

T27425674
Position Surface form Disambiguated ID Type / Status
Subject assassination of Henry IV of France E690476 entity
Predicate location P40 FINISHED
Object Rue de la Ferronnerie
Rue de la Ferronnerie is a historic street in central Paris, France, best known as the site where King Henry IV was assassinated in 1610.
E2292054 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: Rue de la Ferronnerie | Statement: [assassination of Henry IV of France, location, Rue de la Ferronnerie]
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: Rue de la Ferronnerie
Triple: [assassination of Henry IV of France, location, Rue de la Ferronnerie]
Generated description
Rue de la Ferronnerie is a historic street in central Paris, France, best known as the site where King Henry IV was assassinated in 1610.

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_69ef52003fb48190b0f1295246182a86 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62d546b2881909d0acb99ce291de1 completed May 2, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5cb8c38b2c8190a913f3d05eefb51d completed July 19, 2026, 11:45 a.m.
NEDg Description generation batch_6a5cb9270e188190a9a2d24046e81228 completed July 19, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_6a5cb9f27170819082165af56889060f completed July 19, 2026, 11:50 a.m.
Created at: April 27, 2026, 12:40 p.m.