Triple

T1033226
Position Surface form Disambiguated ID Type / Status
Subject Leonardo da Vinci E22299 entity
Predicate deathPlace P21 FINISHED
Object Amboise
Amboise is a historic town in central France on the Loire River, known for its royal château and as the place where Leonardo da Vinci spent his final years.
 E135329 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: Amboise | Statement: [Leonardo da Vinci, deathPlace, Amboise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Amboise
Context triple: [Leonardo da Vinci, deathPlace, Amboise]
  • A. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • B. Chinon
    Chinon is a renowned Loire Valley wine appellation in France, best known for its elegant, medium-bodied red wines primarily made from Cabernet Franc.
  • C. Poissy
    Poissy is a commune in the western suburbs of Paris, France, known for hosting Le Corbusier’s iconic modernist Villa Savoye.
  • D. Châteauroux
    Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
  • E. Melun
    Melun is a historic commune in the Île-de-France region of north-central France, known as a regional administrative center and former royal town southeast of Paris.
  • 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: Amboise
Triple: [Leonardo da Vinci, deathPlace, Amboise]
Generated description
Amboise is a historic town in central France on the Loire River, known for its royal château and as the place where Leonardo da Vinci spent his final years.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Amboise
Target entity description: Amboise is a historic town in central France on the Loire River, known for its royal château and as the place where Leonardo da Vinci spent his final years.
  • A. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • B. Chinon
    Chinon is a renowned Loire Valley wine appellation in France, best known for its elegant, medium-bodied red wines primarily made from Cabernet Franc.
  • C. Poissy
    Poissy is a commune in the western suburbs of Paris, France, known for hosting Le Corbusier’s iconic modernist Villa Savoye.
  • D. Châteauroux
    Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
  • E. Melun
    Melun is a historic commune in the Île-de-France region of north-central France, known as a regional administrative center and former royal town southeast of Paris.
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b812c9948190a37c2b1d3d32ea38 completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f0781e08190bbfd5fad2b122150 completed March 7, 2026, 6:31 p.m.
NEDg Description generation batch_69ac7014d7e08190ba19d67beff96756 completed March 7, 2026, 6:36 p.m.
NED2 Entity disambiguation (via description) batch_69ac707f31408190b8febc2f52d396c4 completed March 7, 2026, 6:37 p.m.
Created at: March 1, 2026, 7:41 p.m.