Triple

T9954059
Position Surface form Disambiguated ID Type / Status
Subject Springfield Police Station façade E195401 entity
Predicate associatedWithCharacter P1481 FINISHED
Object Lou
Lou is a recurring Springfield police officer on the animated television series "The Simpsons," known as Chief Wiggum’s level-headed, deadpan partner.
 E830992 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: Lou | Statement: [Springfield Police Station façade, associatedWithCharacter, Lou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lou
Context triple: [Springfield Police Station façade, associatedWithCharacter, Lou]
  • A. Lou
    Lou is a character from the virtual reality co-op shooter game "After the Fall," set in a post-apocalyptic, frozen Los Angeles overrun by mutated creatures.
  • B. Lou
    Lou is a common diminutive form of the given name Louise.
  • C. Luc
    Luc is the given name of Luc Longley, the Australian former professional basketball player and three-time NBA champion with the Chicago Bulls.
  • D. Lon
    Lon is the family name of Lon Nol, the Cambodian general and politician who led a coup against Prince Norodom Sihanouk and headed the Khmer Republic in the early 1970s.
  • E. Lee
    Lee is a residential district in southeast London known for its suburban character, green spaces, and Victorian and Edwardian housing.
  • 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: Lou
Triple: [Springfield Police Station façade, associatedWithCharacter, Lou]
Generated description
Lou is a recurring Springfield police officer on the animated television series "The Simpsons," known as Chief Wiggum’s level-headed, deadpan partner.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lou
Target entity description: Lou is a recurring Springfield police officer on the animated television series "The Simpsons," known as Chief Wiggum’s level-headed, deadpan partner.
  • A. Lou
    Lou is a common diminutive form of the given name Louise.
  • B. Lou
    Lou is a character from the virtual reality co-op shooter game "After the Fall," set in a post-apocalyptic, frozen Los Angeles overrun by mutated creatures.
  • C. Luc
    Luc is the given name of Luc Longley, the Australian former professional basketball player and three-time NBA champion with the Chicago Bulls.
  • D. Lon
    Lon is the family name of Lon Nol, the Cambodian general and politician who led a coup against Prince Norodom Sihanouk and headed the Khmer Republic in the early 1970s.
  • E. Lee
    Lee is a residential district in southeast London known for its suburban character, green spaces, and Victorian and Edwardian housing.
  • 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_69ca82eaaa008190a54fa1a9f954b9ad completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb694b95481909d049302818e7137 completed April 2, 2026, 12:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2294335208190a0483c4e89abb359 completed April 5, 2026, 9:20 a.m.
NEDg Description generation batch_69d22b1a3e548190887b46540614536a completed April 5, 2026, 9:27 a.m.
NED2 Entity disambiguation (via description) batch_69d22bc3ac5c81908b0696ce94263d36 completed April 5, 2026, 9:30 a.m.
Created at: March 30, 2026, 8:46 p.m.