Triple

T4332254
Position Surface form Disambiguated ID Type / Status
Subject Sharon Robinson E96779 entity
Predicate notableWork P4 FINISHED
Object Caffeine
"Caffeine" is a young adult novel by Sharon Robinson that explores themes of adolescence, family, and personal struggle.
 E431132 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: Caffeine | Statement: [Sharon Robinson, notableWork, Caffeine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Caffeine
Context triple: [Sharon Robinson, notableWork, Caffeine]
  • A. Coffee
    "Coffee" is a song by the American singer-songwriter Miguel, known for its smooth blend of R&B and sensual, atmospheric production.
  • B. Coca
    Coca is a small city in Ecuador that serves as a key gateway to the Amazon rainforest and regional oil operations.
  • C. Cocaine
    Cocaine is a powerful and addictive stimulant drug derived from the coca plant, known for its euphoric effects and significant health and legal risks.
  • D. Mocha
    Mocha is a popular JavaScript test framework used primarily for running unit and integration tests in Node.js and browser-based applications.
  • E. Mocha
    Mocha is a subsidiary peak of the Carihuairazo volcanic massif in the Ecuadorian Andes.
  • 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: Caffeine
Triple: [Sharon Robinson, notableWork, Caffeine]
Generated description
"Caffeine" is a young adult novel by Sharon Robinson that explores themes of adolescence, family, and personal struggle.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Caffeine
Target entity description: "Caffeine" is a young adult novel by Sharon Robinson that explores themes of adolescence, family, and personal struggle.
  • A. Coffee
    "Coffee" is a song by the American singer-songwriter Miguel, known for its smooth blend of R&B and sensual, atmospheric production.
  • B. Coca
    Coca is a small city in Ecuador that serves as a key gateway to the Amazon rainforest and regional oil operations.
  • C. Cocaine
    Cocaine is a powerful and addictive stimulant drug derived from the coca plant, known for its euphoric effects and significant health and legal risks.
  • D. Mocha
    Mocha is a popular JavaScript test framework used primarily for running unit and integration tests in Node.js and browser-based applications.
  • E. Mocha
    Mocha is a subsidiary peak of the Carihuairazo volcanic massif in the Ecuadorian Andes.
  • 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_69b34542fd908190b11b08faad8decfd completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3514dc588819086a4c6d585c1b5b1 completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d0a307388190af4cb98b03e9656d completed March 14, 2026, 9:18 p.m.
NEDg Description generation batch_69b5d12a54e0819081379fd1ee85914b completed March 14, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_69b5d194975481908b029ab106223c6c completed March 14, 2026, 9:22 p.m.
Created at: March 12, 2026, 11:13 p.m.