Triple

T1318477
Position Surface form Disambiguated ID Type / Status
Subject Evelyn Waugh E28160 entity
Predicate notableWork P4 FINISHED
Object Scoop
Scoop is a satirical novel by Evelyn Waugh that lampoons sensationalist journalism and foreign correspondence.
 E150424 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: Scoop | Statement: [Evelyn Waugh, notableWork, Scoop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Scoop
Context triple: [Evelyn Waugh, notableWork, Scoop]
  • A. The Guardian
    The Guardian is a British daily newspaper known for its progressive editorial stance and in-depth coverage of national and international news, culture, and opinion.
  • B. The Gray Lady
    The Gray Lady is a longstanding nickname for The New York Times, reflecting its reputation as a serious, authoritative, and traditional American newspaper.
  • C. The Fifth Estate
    The Fifth Estate is a long-running Canadian investigative journalism television program known for its in-depth reporting and exposés on major public-interest issues.
  • D. The Fifth Estate
    The Fifth Estate is a 2013 biographical thriller film that dramatizes the rise of WikiLeaks and its controversial founder Julian Assange.
  • E. Mr. Papers
    Mr. Papers is a rapper best known for his on-and-off romantic relationship with hip-hop icon Lil' Kim.
  • 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: Scoop
Triple: [Evelyn Waugh, notableWork, Scoop]
Generated description
Scoop is a satirical novel by Evelyn Waugh that lampoons sensationalist journalism and foreign correspondence.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Scoop
Target entity description: Scoop is a satirical novel by Evelyn Waugh that lampoons sensationalist journalism and foreign correspondence.
  • A. The Guardian
    The Guardian is a British daily newspaper known for its progressive editorial stance and in-depth coverage of national and international news, culture, and opinion.
  • B. The Gray Lady
    The Gray Lady is a longstanding nickname for The New York Times, reflecting its reputation as a serious, authoritative, and traditional American newspaper.
  • C. The Fifth Estate
    The Fifth Estate is a long-running Canadian investigative journalism television program known for its in-depth reporting and exposés on major public-interest issues.
  • D. The Fifth Estate
    The Fifth Estate is a 2013 biographical thriller film that dramatizes the rise of WikiLeaks and its controversial founder Julian Assange.
  • E. Mr. Papers
    Mr. Papers is a rapper best known for his on-and-off romantic relationship with hip-hop icon Lil' Kim.
  • 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_69a498532c3481909223b74af2e578df completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c176c89881909e9dc0e34f12f056 completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbaf3cef88190ab1635bc5f452f8b completed March 7, 2026, 11:55 p.m.
NEDg Description generation batch_69acbb5ee684819083f5309dc9771c3a completed March 7, 2026, 11:57 p.m.
NED2 Entity disambiguation (via description) batch_69acbc010cd0819080b1f8695dc0990b completed March 8, 2026, midnight
Created at: March 1, 2026, 7:55 p.m.