Triple

T1342769
Position Surface form Disambiguated ID Type / Status
Subject Martyn Lloyd-Jones E28502 entity
Predicate givenName P17 FINISHED
Object Martyn
Martyn is a masculine given name of Welsh origin, commonly used in English-speaking countries.
E154028 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: Martyn | Statement: [Martyn Lloyd-Jones, givenName, Martyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martyn
Context triple: [Martyn Lloyd-Jones, givenName, Martyn]
  • A. Bevan
    Bevan is a Welsh surname most famously associated with Aneurin Bevan, the Labour politician regarded as the chief architect of the United Kingdom’s National Health Service.
  • B. Myles
    Myles is a masculine given name of English origin, historically associated with figures such as Mayflower military leader Myles Standish.
  • C. Darley Dale
    Darley Dale is a small town and civil parish in the Derbyshire Dales of England, known for its scenic setting near the Peak District and its historic railway heritage.
  • D. Christopher Blake
    Christopher Blake is a stage play written by American playwright Moss Hart, best known for its dramatic exploration of family and marital conflict.
  • E. Thom Mount
    Thom Mount is an American film producer and former president of Universal Pictures known for overseeing and producing a range of influential Hollywood films.
  • 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: Martyn
Triple: [Martyn Lloyd-Jones, givenName, Martyn]
Generated description
Martyn is a masculine given name of Welsh origin, commonly used in English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Martyn
Target entity description: Martyn is a masculine given name of Welsh origin, commonly used in English-speaking countries.
  • A. Bevan
    Bevan is a Welsh surname most famously associated with Aneurin Bevan, the Labour politician regarded as the chief architect of the United Kingdom’s National Health Service.
  • B. Myles
    Myles is a masculine given name of English origin, historically associated with figures such as Mayflower military leader Myles Standish.
  • C. Darley Dale
    Darley Dale is a small town and civil parish in the Derbyshire Dales of England, known for its scenic setting near the Peak District and its historic railway heritage.
  • D. Christopher Blake
    Christopher Blake is a stage play written by American playwright Moss Hart, best known for its dramatic exploration of family and marital conflict.
  • E. Thom Mount
    Thom Mount is an American film producer and former president of Universal Pictures known for overseeing and producing a range of influential Hollywood films.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c2174d048190a6e9380df302265f completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc632cbc88190a64897f1b101c699 completed March 8, 2026, 12:43 a.m.
NEDg Description generation batch_69acc6dbd80881908d640ee204ce9a12 completed March 8, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_69acc8199f508190a86c18ad9085d341 completed March 8, 2026, 12:51 a.m.
Created at: March 1, 2026, 7:56 p.m.