Triple

T52329
Position Surface form Disambiguated ID Type / Status
Subject Georges Longy E1027 entity
Predicate givenName P17 FINISHED
Object Georges
Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
E18182 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: Georges | Statement: [Georges Longy, givenName, Georges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Georges
Context triple: [Georges Longy, givenName, Georges]
  • A. Pierre
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • B. Stephen Sauvestre
    Stephen Sauvestre was a French architect best known for designing the architectural embellishments and final aesthetic of the Eiffel Tower.
  • C. Guillaume
    Guillaume is the French form of the given name William, commonly used in French-speaking countries.
  • D. Charles Léon
    Charles Léon was the illegitimate son of Napoleon Bonaparte and a French servant, known primarily for his connection to the emperor.
  • E. Bertrand
    Bertrand is a masculine given name most famously associated with the British philosopher, logician, and Nobel laureate Bertrand Russell.
  • 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: Georges
Triple: [Georges Longy, givenName, Georges]
Generated description
Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Georges
Target entity description: Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
  • A. Pierre
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • B. Stephen Sauvestre
    Stephen Sauvestre was a French architect best known for designing the architectural embellishments and final aesthetic of the Eiffel Tower.
  • C. Guillaume
    Guillaume is the French form of the given name William, commonly used in French-speaking countries.
  • D. Charles Léon
    Charles Léon was the illegitimate son of Napoleon Bonaparte and a French servant, known primarily for his connection to the emperor.
  • E. Bertrand
    Bertrand is a masculine given name most famously associated with the British philosopher, logician, and Nobel laureate Bertrand Russell.
  • 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_69a2480baefc81909951b14058479aa2 completed Feb. 28, 2026, 1:42 a.m.
NER Named-entity recognition batch_69a24b0382b48190a7ca80ade6d2e270 completed Feb. 28, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2c529506c81908da1e88f04d6b0a0 completed Feb. 28, 2026, 10:36 a.m.
NEDg Description generation batch_69a2c633ed688190937e3603b5bcfac8 completed Feb. 28, 2026, 10:40 a.m.
NED2 Entity disambiguation (via description) batch_69a2c6cb23a88190a134f3820a080201 completed Feb. 28, 2026, 10:43 a.m.
Created at: Feb. 28, 2026, 1:47 a.m.