Triple

T16162347
Position Surface form Disambiguated ID Type / Status
Subject Le Gaulois E392208 entity
Predicate publisher P29 FINISHED
Object Henry de Pène
Henry de Pène was a 19th-century French journalist and writer known for his role in the Parisian press and literary circles.
 E1198170 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: Henry de Pène | Statement: [Le Gaulois, publisher, Henry de Pène]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Henry de Pène
Context triple: [Le Gaulois, publisher, Henry de Pène]
  • A. Edmond Thieffry
    Edmond Thieffry was a pioneering Belgian World War I flying ace and aviation trailblazer who later helped establish early commercial air routes for Sabena.
  • B. Joseph Brocherel
    Joseph Brocherel was a mountaineer known for making the first recorded ascent of Batian, the highest peak of Mount Kenya.
  • C. Joseph Brocherel
    Joseph Brocherel was an Italian mountaineer known for participating in the pioneering ascent of Mount Kenya.
  • D. Charles Le Breton
    Charles Le Breton is a historical figure known primarily as a notable bearer of the French surname "Le Breton," which denotes Breton origin.
  • E. Arthur Malet
    Arthur Malet was a British-born character actor known for his distinctive voice and frequent supporting roles in American film and television, including voice work in animated features.
  • 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: Henry de Pène
Triple: [Le Gaulois, publisher, Henry de Pène]
Generated description
Henry de Pène was a 19th-century French journalist and writer known for his role in the Parisian press and literary circles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Henry de Pène
Target entity description: Henry de Pène was a 19th-century French journalist and writer known for his role in the Parisian press and literary circles.
  • A. Edmond Thieffry
    Edmond Thieffry was a pioneering Belgian World War I flying ace and aviation trailblazer who later helped establish early commercial air routes for Sabena.
  • B. Joseph Brocherel
    Joseph Brocherel was a mountaineer known for making the first recorded ascent of Batian, the highest peak of Mount Kenya.
  • C. Joseph Brocherel
    Joseph Brocherel was an Italian mountaineer known for participating in the pioneering ascent of Mount Kenya.
  • D. Charles Le Breton
    Charles Le Breton is a historical figure known primarily as a notable bearer of the French surname "Le Breton," which denotes Breton origin.
  • E. Arthur Malet
    Arthur Malet was a British-born character actor known for his distinctive voice and frequent supporting roles in American film and television, including voice work in animated features.
  • 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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21e5ffba88190b9dc7bb9afb6fdf2 completed April 17, 2026, 11:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7b33f3481909fe856b8be7d9bcd completed May 10, 2026, 3:12 a.m.
NEDg Description generation batch_69fff86a556c819096bc008e1ca76e8c completed May 10, 2026, 3:15 a.m.
NED2 Entity disambiguation (via description) batch_69fff926120081909f1042bf3a16ea10 completed May 10, 2026, 3:19 a.m.
Created at: April 10, 2026, 5:02 a.m.