Triple

T11784482
Position Surface form Disambiguated ID Type / Status
Subject Nantua E280235 entity
Predicate hasDemonym P191 FINISHED
Object Nantuatien
Nantuatien is the French demonym for an inhabitant of the town of Nantua in eastern France.
 E946345 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: Nantuatien | Statement: [Nantua, hasDemonym, Nantuatien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nantuatien
Context triple: [Nantua, hasDemonym, Nantuatien]
  • A. Huating
    Huating is a historical town that once served as the name and administrative center of what is now Shanghai’s Songjiang District.
  • B. Numata
    Numata is a city in Gunma Prefecture, Japan, known as a gateway to the Mount Akagi and Oze National Park areas.
  • C. Nobatae
    The Nobatae were an ancient Nubian people who inhabited parts of Lower Nubia and later formed the core population of the early medieval kingdom of Nobatia in what is now southern Egypt and northern Sudan.
  • D. Nain
    Nain is a remote coastal town in northern Labrador, Canada, known as the administrative center of the Inuit region of Nunatsiavut.
  • E. Nain
    Nain is a renowned Iranian town famous for producing high-quality, finely knotted Persian carpets characterized by intricate designs and a typically light color palette.
  • 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: Nantuatien
Triple: [Nantua, hasDemonym, Nantuatien]
Generated description
Nantuatien is the French demonym for an inhabitant of the town of Nantua in eastern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nantuatien
Target entity description: Nantuatien is the French demonym for an inhabitant of the town of Nantua in eastern France.
  • A. Huating
    Huating is a historical town that once served as the name and administrative center of what is now Shanghai’s Songjiang District.
  • B. Numata
    Numata is a city in Gunma Prefecture, Japan, known as a gateway to the Mount Akagi and Oze National Park areas.
  • C. Nobatae
    The Nobatae were an ancient Nubian people who inhabited parts of Lower Nubia and later formed the core population of the early medieval kingdom of Nobatia in what is now southern Egypt and northern Sudan.
  • D. Nain
    Nain is a remote coastal town in northern Labrador, Canada, known as the administrative center of the Inuit region of Nunatsiavut.
  • E. Nain
    Nain is a renowned Iranian town famous for producing high-quality, finely knotted Persian carpets characterized by intricate designs and a typically light color palette.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a585795c8190aa8a5edf0d99b47f completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f090d861f481909b920197a3d60e28 completed April 28, 2026, 10:50 a.m.
NEDg Description generation batch_69f0bd3f39608190b29027b30664bd9c completed April 28, 2026, 1:59 p.m.
NED2 Entity disambiguation (via description) batch_69f0ef5afd448190953b5d9929478132 completed April 28, 2026, 5:33 p.m.
Created at: April 8, 2026, 9:42 p.m.