Triple

T4684156
Position Surface form Disambiguated ID Type / Status
Subject Slim Keith E103877 entity
Predicate nickname P55 FINISHED
Object Slim
Slim is the nickname of Slim Keith, a prominent American socialite and fashion icon of the mid-20th century known for her influence in high society and style.
 E460511 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: Slim | Statement: [Slim Keith, nickname, Slim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Slim
Context triple: [Slim Keith, nickname, Slim]
  • A. Slim
    Slim is the tall, sarcastic stick insect who performs as a reluctant clown in the circus troupe in Pixar's animated film "A Bug's Life."
  • B. Slim
    Slim is a highly respected, compassionate, and insightful mule driver on the ranch in John Steinbeck’s novel "Of Mice and Men," often serving as a moral authority among the workers.
  • C. Slim
    Slim is a lightweight Ruby templating engine known for its minimal syntax and fast rendering performance.
  • D. SLIM
    SLIM is a Japanese lunar lander mission developed by JAXA to demonstrate high-precision, lightweight Moon-landing technology.
  • E. Slim Flash
    Slim Flash is a lightweight flash messaging component designed to integrate with the Slim Framework for handling temporary user notifications between HTTP requests.
  • 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: Slim
Triple: [Slim Keith, nickname, Slim]
Generated description
Slim is the nickname of Slim Keith, a prominent American socialite and fashion icon of the mid-20th century known for her influence in high society and style.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Slim
Target entity description: Slim is the nickname of Slim Keith, a prominent American socialite and fashion icon of the mid-20th century known for her influence in high society and style.
  • A. Slim
    Slim is the tall, sarcastic stick insect who performs as a reluctant clown in the circus troupe in Pixar's animated film "A Bug's Life."
  • B. Slim
    Slim is a highly respected, compassionate, and insightful mule driver on the ranch in John Steinbeck’s novel "Of Mice and Men," often serving as a moral authority among the workers.
  • C. Slim
    Slim is a lightweight Ruby templating engine known for its minimal syntax and fast rendering performance.
  • D. SLIM
    SLIM is a Japanese lunar lander mission developed by JAXA to demonstrate high-precision, lightweight Moon-landing technology.
  • E. Slim Flash
    Slim Flash is a lightweight flash messaging component designed to integrate with the Slim Framework for handling temporary user notifications between HTTP requests.
  • 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_69bd43debbf08190b4bc372e286ec234 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63829b048190a2044de900ef7a69 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03b07664819097d959fde1b0585b completed March 21, 2026, 2:34 a.m.
NEDg Description generation batch_69be04dc48b08190947cde715f87a4d0 completed March 21, 2026, 2:39 a.m.
NED2 Entity disambiguation (via description) batch_69be05742e248190bb0e846189dfcfb5 completed March 21, 2026, 2:41 a.m.
Created at: March 20, 2026, 1:16 p.m.