Triple

T9965630
Position Surface form Disambiguated ID Type / Status
Subject Poésies E195675 entity
Predicate hasPart P35 FINISHED
Object Aumône
"Aumône" is a poem included in the collection *Poésies*, likely reflecting themes of charity or almsgiving.
 E833011 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: Aumône | Statement: [Poésies, hasPart, Aumône]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Aumône
Context triple: [Poésies, hasPart, Aumône]
  • A. Saint-Ambroise
    Saint-Ambroise is a small municipality in the Saguenay–Lac-Saint-Jean region of Quebec, Canada, known for its agricultural character and rural setting.
  • B. Boncourt
    Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
  • C. Ermontoise
    Ermontoise is the French demonym referring to a female inhabitant or native of the town of Ermont in France.
  • D. Fremault
    Fremault is the surname of American film and television actress Anita Louise.
  • E. Saint-Amour
    Saint-Amour is one of the ten Beaujolais crus in eastern France, known for producing aromatic, fruit-forward red wines primarily from the Gamay grape.
  • 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: Aumône
Triple: [Poésies, hasPart, Aumône]
Generated description
"Aumône" is a poem included in the collection *Poésies*, likely reflecting themes of charity or almsgiving.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Aumône
Target entity description: "Aumône" is a poem included in the collection *Poésies*, likely reflecting themes of charity or almsgiving.
  • A. Saint-Ambroise
    Saint-Ambroise is a small municipality in the Saguenay–Lac-Saint-Jean region of Quebec, Canada, known for its agricultural character and rural setting.
  • B. Boncourt
    Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
  • C. Ermontoise
    Ermontoise is the French demonym referring to a female inhabitant or native of the town of Ermont in France.
  • D. Fremault
    Fremault is the surname of American film and television actress Anita Louise.
  • E. Saint-Amour
    Saint-Amour is one of the ten Beaujolais crus in eastern France, known for producing aromatic, fruit-forward red wines primarily from the Gamay grape.
  • 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_69ca82ebd1288190912f9e4482d1fa35 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb71c38488190a6f3cda11994f6a2 completed April 2, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23da2d7988190b8603ddb151996d9 completed April 5, 2026, 10:46 a.m.
NEDg Description generation batch_69d23eb1c1f481908404225dcccd0697 completed April 5, 2026, 10:51 a.m.
NED2 Entity disambiguation (via description) batch_69d242aea6a08190a73a836e59865c35 completed April 5, 2026, 11:08 a.m.
Created at: March 30, 2026, 8:47 p.m.