Triple

T4432913
Position Surface form Disambiguated ID Type / Status
Subject Charlene E95375 entity
Predicate hasDiminutive P456 FINISHED
Object Char
Char is a common English diminutive or nickname typically derived from given names such as Charlene, Charlotte, or Charlize.
 E440564 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: Char | Statement: [Charlene, hasDiminutive, Char]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Char
Context triple: [Charlene, hasDiminutive, Char]
  • A. Chan
    Chan is a common Chinese surname shared by many notable individuals across various fields worldwide.
  • B. Charlie
    Charlie was the third nuclear test in the U.S. Operation Crossroads series, planned as an underwater detonation to study the effects of nuclear weapons on naval vessels.
  • C. Charlie
    Charlie is Dory’s loving but forgetful father in the animated film "Finding Dory," known for his patience, optimism, and inventive ways of helping her cope with memory loss.
  • D. Charlie
    Charlie is the fictional Boston subway rider in the folk song "Charlie on the MTA," known for being unable to get off the train because he lacks the fare to exit.
  • E. Chuck
    Chuck is an American action-comedy television series that blends spy drama with workplace humor, centered on an ordinary computer geek who accidentally becomes a government asset.
  • 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: Char
Triple: [Charlene, hasDiminutive, Char]
Generated description
Char is a common English diminutive or nickname typically derived from given names such as Charlene, Charlotte, or Charlize.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Char
Target entity description: Char is a common English diminutive or nickname typically derived from given names such as Charlene, Charlotte, or Charlize.
  • A. Chan
    Chan is a common Chinese surname shared by many notable individuals across various fields worldwide.
  • B. Charlie
    Charlie was the third nuclear test in the U.S. Operation Crossroads series, planned as an underwater detonation to study the effects of nuclear weapons on naval vessels.
  • C. Charlie
    Charlie is Dory’s loving but forgetful father in the animated film "Finding Dory," known for his patience, optimism, and inventive ways of helping her cope with memory loss.
  • D. Charlie
    Charlie is the fictional Boston subway rider in the folk song "Charlie on the MTA," known for being unable to get off the train because he lacks the fare to exit.
  • E. Chuck
    Chuck is an American action-comedy television series that blends spy drama with workplace humor, centered on an ordinary computer geek who accidentally becomes a government asset.
  • 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_69b3453c2a0c8190926b574c90766db9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3556cd83881908547aa311c4f17fa completed March 13, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6137171148190b77a6f783d5cf315 completed March 15, 2026, 2:03 a.m.
NEDg Description generation batch_69b6177d1a588190991fddf506239d22 completed March 15, 2026, 2:20 a.m.
NED2 Entity disambiguation (via description) batch_69b61b6bc1448190b30d444a821bb1a5 completed March 15, 2026, 2:37 a.m.
Created at: March 12, 2026, 11:31 p.m.