Triple

T968766
Position Surface form Disambiguated ID Type / Status
Subject MaddAddam E20897 entity
Predicate mainCharacter P1183 FINISHED
Object Ren
Ren is a central character in Margaret Atwood’s dystopian MaddAddam trilogy, known for her experiences as a sex worker and survivor in a bioengineered, post-apocalyptic world.
 E114762 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: Ren | Statement: [MaddAddam, mainCharacter, Ren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ren
Context triple: [MaddAddam, mainCharacter, Ren]
  • A. REN
    REN is a blockchain-based project and protocol focused on enabling cross-chain liquidity and interoperability between different cryptocurrency networks.
  • B. Rob
    Rob is a common shortened form of the given name Robert, frequently used as an informal or familiar first name.
  • C. Ryan
    Ryan is a masculine given name of Irish origin that is widely used in English-speaking countries.
  • D. Resh
    Resh is the twentieth letter of the Hebrew alphabet, representing an "r" sound and used in both Hebrew writing and numerology.
  • E. RM
    RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
  • 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: Ren
Triple: [MaddAddam, mainCharacter, Ren]
Generated description
Ren is a central character in Margaret Atwood’s dystopian MaddAddam trilogy, known for her experiences as a sex worker and survivor in a bioengineered, post-apocalyptic world.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ren
Target entity description: Ren is a central character in Margaret Atwood’s dystopian MaddAddam trilogy, known for her experiences as a sex worker and survivor in a bioengineered, post-apocalyptic world.
  • A. REN
    REN is a blockchain-based project and protocol focused on enabling cross-chain liquidity and interoperability between different cryptocurrency networks.
  • B. Rob
    Rob is a common shortened form of the given name Robert, frequently used as an informal or familiar first name.
  • C. Ryan
    Ryan is a masculine given name of Irish origin that is widely used in English-speaking countries.
  • D. Resh
    Resh is the twentieth letter of the Hebrew alphabet, representing an "r" sound and used in both Hebrew writing and numerology.
  • E. RM
    RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
  • 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_69a493b33d2c81909c52c369d3ca8436 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b4481f508190adcf0a965a23862c completed March 1, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac17055f008190a5011d9b23bd3858 completed March 7, 2026, 12:16 p.m.
NEDg Description generation batch_69ac17c2e6f48190be6fce7f279957c4 completed March 7, 2026, 12:19 p.m.
NED2 Entity disambiguation (via description) batch_69ac1844acec81909859605d2421a588 completed March 7, 2026, 12:21 p.m.
Created at: March 1, 2026, 7:40 p.m.