Triple

T11448184
Position Surface form Disambiguated ID Type / Status
Subject George S. Houston E271318 entity
Predicate givenName P17 FINISHED
Object George
George is a common masculine given name of Greek origin, widely used in English-speaking and many other cultures.
E372348 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: George | Statement: [George S. Houston, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [George S. Houston, givenName, George]
  • A. George
    George is the given first name of the fictional character Gob Bluth from the television series "Arrested Development."
  • B. George
    George is the given name of George Stanley, 9th Baron Strange, an English nobleman and politician of the late 15th century.
  • C. George
    George is a middle-aged, embittered history professor whose caustic wit and psychological games drive the intense marital drama in Edward Albee’s play "Who’s Afraid of Virginia Woolf?".
  • D. George
    George is the given name of George Washington Gale Ferris Jr., the American engineer best known for inventing the original Ferris wheel.
  • E. George
    George is the given name of George Carnegie, 6th Earl of Northesk, a Scottish nobleman and naval officer in the Royal Navy.
  • 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: George
Triple: [George S. Houston, givenName, George]
Generated description
George is a common masculine given name of Greek origin, widely used in English-speaking and many other cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: George
Target entity description: George is a common masculine given name of Greek origin, widely used in English-speaking and many other cultures.
  • A. George
    George is a masculine given name of Greek origin, commonly used in English-speaking countries and borne by numerous historical and contemporary figures.
  • B. George
    George is a male given name commonly used in English-speaking countries and borne by numerous historical figures, including kings, presidents, and cultural icons.
  • C. George
    George is a common masculine given name of Greek origin, meaning "farmer" or "earthworker."
  • D. George chosen
    George is a masculine given name of Greek origin meaning "farmer" or "earthworker," widely used in English-speaking countries and beyond.
  • E. George
    George is a common English surname of likely Greek and Latin origin, associated with numerous notable historical and contemporary figures.
  • F. None of above.

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_69d6aadff8888190a13f253f0d460874 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d81c6d4890819082fb4a670feb2629 completed April 9, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5e8f8049881909c1a52101e4620b3 completed April 20, 2026, 8:51 a.m.
NEDg Description generation batch_69e5f1557e9c8190b53ce391793b2c7f completed April 20, 2026, 9:26 a.m.
NED2 Entity disambiguation (via description) batch_69e5f863bf7c81908969ed0a5b99f032 completed April 20, 2026, 9:56 a.m.
Created at: April 8, 2026, 9:35 p.m.