Triple

T32717017
Position Surface form Disambiguated ID Type / Status
Subject Jean-Rodolphe Perronet E836546 entity
Predicate notableWork P4 FINISHED
Object Pont de Mantes
Pont de Mantes is an 18th-century French bridge designed by engineer Jean-Rodolphe Perronet, exemplifying early modern bridge engineering and elegant stone-arch construction.
E2024654 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: Pont de Mantes | Statement: [Jean-Rodolphe Perronet, notableWork, Pont de Mantes]
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: Pont de Mantes
Triple: [Jean-Rodolphe Perronet, notableWork, Pont de Mantes]
Generated description
Pont de Mantes is an 18th-century French bridge designed by engineer Jean-Rodolphe Perronet, exemplifying early modern bridge engineering and elegant stone-arch construction.

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_69f34935455881909088975d79460418 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c88759ac81909146f11012ed7ee5 completed May 3, 2026, 4:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34b156a53c8190abe5cb37f5be50af completed June 19, 2026, 3:02 a.m.
NEDg Description generation batch_6a34b594e000819082d09b7d126636d8 completed June 19, 2026, 3:20 a.m.
NED2 Entity disambiguation (via description) batch_6a34b5c121c88190896fafac83d27b9b completed June 19, 2026, 3:21 a.m.
Created at: May 1, 2026, 1:11 a.m.