Triple

T15814647
Position Surface form Disambiguated ID Type / Status
Subject Polly Moran E383443 entity
Predicate notableWork P4 FINISHED
Object Caught Short
Caught Short is a 1930 American pre-Code comedy film best known for featuring character actress Polly Moran in a prominent comedic role.
E1177913 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: Caught Short | Statement: [Polly Moran, notableWork, Caught Short]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caught Short
Context triple: [Polly Moran, notableWork, Caught Short]
  • A. Caught Up
    "Caught Up" is a soulful R&B track by John Legend from his album *Love in the Future*, showcasing his smooth vocals and romantic, introspective lyricism.
  • B. Caught Up
    "Caught Up" is an R&B song by Usher from his 2004 album *Confessions*, known for its upbeat tempo and themes of being unexpectedly overwhelmed by love.
  • C. Short Cuts
    Short Cuts is a Toronto International Film Festival program showcasing a curated selection of international and Canadian short films across genres and styles.
  • D. Short Cuts
    Short Cuts is a 1993 ensemble drama film directed by Robert Altman, adapted from Raymond Carver’s short stories and known for its interwoven narratives about Los Angeles residents.
  • E. Short Cuts
    Short Cuts is a regular column in the London Review of Books featuring brief, incisive commentary on current events, culture, and politics.
  • 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: Caught Short
Triple: [Polly Moran, notableWork, Caught Short]
Generated description
Caught Short is a 1930 American pre-Code comedy film best known for featuring character actress Polly Moran in a prominent comedic role.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Caught Short
Target entity description: Caught Short is a 1930 American pre-Code comedy film best known for featuring character actress Polly Moran in a prominent comedic role.
  • A. Caught Up
    "Caught Up" is a soulful R&B track by John Legend from his album *Love in the Future*, showcasing his smooth vocals and romantic, introspective lyricism.
  • B. Caught Up
    "Caught Up" is an R&B song by Usher from his 2004 album *Confessions*, known for its upbeat tempo and themes of being unexpectedly overwhelmed by love.
  • C. Short Cuts
    Short Cuts is a Toronto International Film Festival program showcasing a curated selection of international and Canadian short films across genres and styles.
  • D. Short Cuts
    Short Cuts is a regular column in the London Review of Books featuring brief, incisive commentary on current events, culture, and politics.
  • E. Short Cuts
    Short Cuts is a 1993 ensemble drama film directed by Robert Altman, adapted from Raymond Carver’s short stories and known for its interwoven narratives about Los Angeles residents.
  • 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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0c4a1571881909488728f123865ad completed April 16, 2026, 11:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff9993c86c8190b1d106af7537080a completed May 9, 2026, 8:31 p.m.
NEDg Description generation batch_69ff9a32d6bc81909d8023de562a2517 completed May 9, 2026, 8:33 p.m.
NED2 Entity disambiguation (via description) batch_69ff9adb25448190b805046ae6c3ee17 completed May 9, 2026, 8:36 p.m.
Created at: April 10, 2026, 4:49 a.m.