Triple

T8170931
Position Surface form Disambiguated ID Type / Status
Subject Hôtel de Sully E190816 entity
Predicate commissionedBy P27 FINISHED
Object Mesme Gallet
Mesme Gallet was a 17th-century French financier and royal official known for commissioning the prestigious Hôtel de Sully in Paris.
E716048 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: Mesme Gallet | Statement: [Hôtel de Sully, commissionedBy, Mesme Gallet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mesme Gallet
Context triple: [Hôtel de Sully, commissionedBy, Mesme Gallet]
  • A. Las Galletas
    Las Galletas is a small coastal resort town in southern Tenerife, Spain, known for its fishing harbor, relaxed atmosphere, and oceanfront promenades.
  • B. Bisco
    Bisco is a popular Japanese biscuit snack brand known for its cream-filled sandwich cookies marketed as a nutritious treat for children.
  • C. Ceci
    Ceci is a given name or nickname, typically used as a shortened, informal form of the name Cecilia.
  • D. Alma Pudden
    Alma Pudden is a fictional schoolgirl character from Enid Blyton’s "St. Clare’s" series, known for attending the boarding school of the same name.
  • E. Minna Gombell
    Minna Gombell was an American stage and film actress active in the 1930s and 1940s, known for her character roles in Hollywood productions.
  • 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: Mesme Gallet
Triple: [Hôtel de Sully, commissionedBy, Mesme Gallet]
Generated description
Mesme Gallet was a 17th-century French financier and royal official known for commissioning the prestigious Hôtel de Sully in Paris.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mesme Gallet
Target entity description: Mesme Gallet was a 17th-century French financier and royal official known for commissioning the prestigious Hôtel de Sully in Paris.
  • A. Las Galletas
    Las Galletas is a small coastal resort town in southern Tenerife, Spain, known for its fishing harbor, relaxed atmosphere, and oceanfront promenades.
  • B. Bisco
    Bisco is a popular Japanese biscuit snack brand known for its cream-filled sandwich cookies marketed as a nutritious treat for children.
  • C. Ceci
    Ceci is a given name or nickname, typically used as a shortened, informal form of the name Cecilia.
  • D. Alma Pudden
    Alma Pudden is a fictional schoolgirl character from Enid Blyton’s "St. Clare’s" series, known for attending the boarding school of the same name.
  • E. Minna Gombell
    Minna Gombell was an American stage and film actress active in the 1930s and 1940s, known for her character roles in Hollywood productions.
  • 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_69ca82c1c0a08190bf8692b4d91a03ca completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb48056d0c819094575090a41e0083 completed March 31, 2026, 4:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbf5cfd588190b12ef9b5799ffd88 completed April 1, 2026, 6:46 a.m.
NEDg Description generation batch_69ccc312a8608190b899394752ef375f completed April 1, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69ccd84893488190ae5376524650d5c4 completed April 1, 2026, 8:33 a.m.
Created at: March 30, 2026, 5:39 p.m.