Triple

T15178390
Position Surface form Disambiguated ID Type / Status
Subject Là-bas E362672 entity
Predicate character P662 FINISHED
Object Des Hermies
Des Hermies is a skeptical, scientifically minded doctor who serves as a cynical commentator on society and religion in Joris-Karl Huysmans’ novel "Là-bas."
 E1141160 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: Des Hermies | Statement: [Là-bas, character, Des Hermies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Des Hermies
Context triple: [Là-bas, character, Des Hermies]
  • A. Margeride
    Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • B. Le Brusquet
    Le Brusquet is a small commune in southeastern France situated in the Alpes-de-Haute-Provence department.
  • C. Le Bémont
    Le Bémont is a small municipality in the Jura canton of Switzerland, situated on the Franches-Montagnes plateau and known for its rural, pastoral landscape.
  • D. Le Guignon
    Le Guignon is a poem by French writer Charles Baudelaire, included among his early poetic works.
  • E. La Paillade
    La Paillade is the traditional nickname of French football club Montpellier HSC, widely used by supporters and media to refer to the team.
  • 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: Des Hermies
Triple: [Là-bas, character, Des Hermies]
Generated description
Des Hermies is a skeptical, scientifically minded doctor who serves as a cynical commentator on society and religion in Joris-Karl Huysmans’ novel "Là-bas."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Des Hermies
Target entity description: Des Hermies is a skeptical, scientifically minded doctor who serves as a cynical commentator on society and religion in Joris-Karl Huysmans’ novel "Là-bas."
  • A. Margeride
    Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • B. Le Brusquet
    Le Brusquet is a small commune in southeastern France situated in the Alpes-de-Haute-Provence department.
  • C. Le Bémont
    Le Bémont is a small municipality in the Jura canton of Switzerland, situated on the Franches-Montagnes plateau and known for its rural, pastoral landscape.
  • D. Le Guignon
    Le Guignon is a poem by French writer Charles Baudelaire, included among his early poetic works.
  • E. La Paillade
    La Paillade is the traditional nickname of French football club Montpellier HSC, widely used by supporters and media to refer to the team.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00663b4148190b647592eda315d1d completed April 15, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec89061548190b0b10da00b8d937e completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69fec91a2d708190bcc67793c46b2a61 completed May 9, 2026, 5:41 a.m.
NED2 Entity disambiguation (via description) batch_69feca0d38088190910dbf4f2538a9d4 completed May 9, 2026, 5:45 a.m.
Created at: April 10, 2026, 3:09 a.m.