Triple

T3677927
Position Surface form Disambiguated ID Type / Status
Subject Mulhouse E78039 entity
Predicate demonym P191 FINISHED
Object Mulhousien
Mulhousien is the French term for an inhabitant or native of the city of Mulhouse in northeastern France.
 E379016 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: Mulhousien | Statement: [Mulhouse, demonym, Mulhousien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mulhousien
Context triple: [Mulhouse, demonym, Mulhousien]
  • A. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • B. Montgomeris
    Montgomeris is a variant form of the surname Montgomery, historically associated with Scottish and Norman lineages.
  • C. Nantz
    Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
  • D. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • E. Muscoy
    Muscoy is an unincorporated community in San Bernardino County, California, known for its semi-rural character within the Inland Empire region.
  • 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: Mulhousien
Triple: [Mulhouse, demonym, Mulhousien]
Generated description
Mulhousien is the French term for an inhabitant or native of the city of Mulhouse in northeastern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mulhousien
Target entity description: Mulhousien is the French term for an inhabitant or native of the city of Mulhouse in northeastern France.
  • A. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • B. Montgomeris
    Montgomeris is a variant form of the surname Montgomery, historically associated with Scottish and Norman lineages.
  • C. Nantz
    Nantz is the surname of Jim Nantz, a prominent American sportscaster best known for his long-running work with CBS Sports covering events like the NFL, NCAA basketball, and The Masters.
  • D. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • E. Muscoy
    Muscoy is an unincorporated community in San Bernardino County, California, known for its semi-rural character within the Inland Empire region.
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc46599188190a046eddb0d85c483 completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3a50d40819081aad0c72bcaee9d completed March 14, 2026, 2:10 a.m.
NEDg Description generation batch_69b4c451a5048190bfd4675cd17de655 completed March 14, 2026, 2:13 a.m.
NED2 Entity disambiguation (via description) batch_69b4c494ad80819084d6aa10fe62a63b completed March 14, 2026, 2:14 a.m.
Created at: March 8, 2026, 3:25 p.m.