Triple

T13590487
Position Surface form Disambiguated ID Type / Status
Subject Agen E324679 entity
Predicate hasDemonym P191 FINISHED
Object Agenaise
Agenaise is the French demonym referring to a female inhabitant or native of the city of Agen in southwestern France.
 E1048727 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: Agenaise | Statement: [Agen, hasDemonym, Agenaise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Agenaise
Context triple: [Agen, hasDemonym, Agenaise]
  • A. Gerhardine
    Gerhardine is the given name of Gerdy Troost, a German architect and interior designer known for her close professional association with the Nazi regime.
  • B. Antoinette
    Antoinette is a feminine given name of French origin, historically associated with nobility and later borne by various notable figures in the arts and public life.
  • C. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • D. Agathé
    Agathé is the ancient Greek name for the historic Mediterranean port city now known as Agde in southern France.
  • E. Axelina
    Axelina is a feminine given name of Scandinavian origin, used as one of the personal names of Carin Axelina Hulda Fock.
  • 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: Agenaise
Triple: [Agen, hasDemonym, Agenaise]
Generated description
Agenaise is the French demonym referring to a female inhabitant or native of the city of Agen in southwestern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Agenaise
Target entity description: Agenaise is the French demonym referring to a female inhabitant or native of the city of Agen in southwestern France.
  • A. Gerhardine
    Gerhardine is the given name of Gerdy Troost, a German architect and interior designer known for her close professional association with the Nazi regime.
  • B. Antoinette
    Antoinette is a feminine given name of French origin, historically associated with nobility and later borne by various notable figures in the arts and public life.
  • C. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • D. Agathé
    Agathé is the ancient Greek name for the historic Mediterranean port city now known as Agde in southern France.
  • E. Axelina
    Axelina is a feminine given name of Scandinavian origin, used as one of the personal names of Carin Axelina Hulda Fock.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb055cc98819091fab597b69e5e3e completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bc347b881908267455f3bdd50e8 completed May 3, 2026, 3:37 p.m.
NEDg Description generation batch_69f77642e4b881909915c686a0d6c6fa completed May 3, 2026, 4:22 p.m.
NED2 Entity disambiguation (via description) batch_69f778f01700819099c3e9cbc84f29e4 completed May 3, 2026, 4:33 p.m.
Created at: April 9, 2026, 9:49 p.m.