Triple

T14552276
Position Surface form Disambiguated ID Type / Status
Subject Moss E341447 entity
Predicate hasNotableBearer P458 FINISHED
Object Malcolm Moss
Malcolm Moss is a British Conservative politician who served as Member of Parliament for North East Cambridgeshire from 1987 to 2010.
E1111437 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: Malcolm Moss | Statement: [Moss, hasNotableBearer, Malcolm Moss]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malcolm Moss
Context triple: [Moss, hasNotableBearer, Malcolm Moss]
  • A. Malcolm Moore
    Malcolm Moore is a musician known for his performance work associated with the album "All the Lost Souls."
  • B. Malcolm Simpson
    Malcolm Simpson is a notable individual distinguished enough to be recognized as a prominent bearer of the Simpson surname.
  • C. John Moss
    John Moss is a tough, streetwise New York City detective who serves as one of the main protagonists in the action-comedy film "The Hard Way."
  • D. Malcolm Sharp
    Malcolm Sharp is a relatively obscure individual whose specific achievements or public role are not widely documented.
  • E. Malcolm McDonald
    Malcolm McDonald is a British marketing scholar and author renowned for his influential work on marketing planning and strategy.
  • 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: Malcolm Moss
Triple: [Moss, hasNotableBearer, Malcolm Moss]
Generated description
Malcolm Moss is a British Conservative politician who served as Member of Parliament for North East Cambridgeshire from 1987 to 2010.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Malcolm Moss
Target entity description: Malcolm Moss is a British Conservative politician who served as Member of Parliament for North East Cambridgeshire from 1987 to 2010.
  • A. Malcolm Moore
    Malcolm Moore is a musician known for his performance work associated with the album "All the Lost Souls."
  • B. Malcolm Simpson
    Malcolm Simpson is a notable individual distinguished enough to be recognized as a prominent bearer of the Simpson surname.
  • C. John Moss
    John Moss is a tough, streetwise New York City detective who serves as one of the main protagonists in the action-comedy film "The Hard Way."
  • D. Malcolm Sharp
    Malcolm Sharp is a relatively obscure individual whose specific achievements or public role are not widely documented.
  • E. Malcolm McDonald
    Malcolm McDonald is a British marketing scholar and author renowned for his influential work on marketing planning and strategy.
  • 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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2ee34208190bf040a513767c958 completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5c3d1d881909ed7e75aae7b08d9 completed May 8, 2026, 12:23 p.m.
NEDg Description generation batch_69fdd74cc4048190bae5f75d922c9618 completed May 8, 2026, 12:30 p.m.
NED2 Entity disambiguation (via description) batch_69fdd7bd20748190b9145ef14ce2759b completed May 8, 2026, 12:31 p.m.
Created at: April 10, 2026, 1:23 a.m.