Triple

T13984937
Position Surface form Disambiguated ID Type / Status
Subject Sims E336413 entity
Predicate derivedFrom P909 FINISHED
Object Simon
Simon is a given name of Hebrew origin that has been widely used across cultures and languages, often associated with various historical, religious, and fictional figures.
 E449149 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: Simon | Statement: [Sims, derivedFrom, Simon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Simon
Context triple: [Sims, derivedFrom, Simon]
  • A. Simon
    Simon is a fictional character from the animated television series "The Seasons."
  • B. Simon
    Simon is the given name of Simon Bolivar Buckner Jr., a U.S. Army lieutenant general who was killed in action while commanding forces during the Battle of Okinawa in World War II.
  • C. Simon
    Simon is a common surname of English and Jewish origin borne by numerous notable individuals across politics, business, arts, and sciences.
  • D. Simon
    Simon is a sleazy used-car salesman and comic-relief character in the action-comedy film "True Lies," who pretends to be a secret agent to seduce women.
  • E. Simon
    Simon is the young, initially timid but ultimately heroic protagonist of the anime series Tengen Toppa Gurren Lagann, known for piloting powerful mecha and embodying themes of growth and determination.
  • 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: Simon
Triple: [Sims, derivedFrom, Simon]
Generated description
Simon is a given name of Hebrew origin that has been widely used across cultures and languages, often associated with various historical, religious, and fictional figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Simon
Target entity description: Simon is a given name of Hebrew origin that has been widely used across cultures and languages, often associated with various historical, religious, and fictional figures.
  • A. Simon chosen
    Simon is a common masculine given name of Hebrew origin, widely used in many cultures and languages.
  • B. Simon
    Simon is a common surname of English and Jewish origin borne by numerous notable individuals across politics, business, arts, and sciences.
  • C. Simon
    Simon is the given name of Simon Bolivar Buckner Jr., a U.S. Army lieutenant general who was killed in action while commanding forces during the Battle of Okinawa in World War II.
  • D. Simon
    Simon is a fictional character from the animated television series "The Seasons."
  • E. Simon
    Simon is the young, initially timid but ultimately heroic protagonist of the anime series Tengen Toppa Gurren Lagann, known for piloting powerful mecha and embodying themes of growth and determination.
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ea3e5a081908ed8ead108139252 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc32593e08190a1fe8466705c7fe8 completed May 6, 2026, 10:39 p.m.
NEDg Description generation batch_69fc4348617881908262390a447ad7af completed May 7, 2026, 7:46 a.m.
NED2 Entity disambiguation (via description) batch_69fc446397988190bb0e415680312ac0 completed May 7, 2026, 7:50 a.m.
Created at: April 9, 2026, 10:18 p.m.