Triple

T5214534
Position Surface form Disambiguated ID Type / Status
Subject Craig Gillespie E117716 entity
Predicate directed P7373 FINISHED
Object Mr. Woodcock
Mr. Woodcock is a 2007 American comedy film about a man who discovers that his overbearing former gym teacher is engaged to his mother.
 E503720 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: Mr. Woodcock | Statement: [Craig Gillespie, directed, Mr. Woodcock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mr. Woodcock
Context triple: [Craig Gillespie, directed, Mr. Woodcock]
  • A. Mr. Jones
    "Mr. Jones" is a hit alternative rock song by Counting Crows, known for its introspective lyrics about fame, dreams, and identity.
  • B. Mr. Brown
    Mr. Brown is the kind-hearted but often flustered father figure from the "Paddington" film series.
  • C. Mr. Sparks
    Mr. Sparks is a friendly, mechanically skilled character in the Noddy children's stories who often helps fix things in Toyland.
  • D. Mr. Skeffington
    Mr. Skeffington is a 1944 drama film starring Bette Davis, known for its exploration of vanity, marriage, and personal transformation.
  • E. Mr. Harling
    Mr. Harling is a prosperous, energetic merchant and the head of the Harling family in Willa Cather’s novel "My Ántonia," known for his strict yet fundamentally kind-hearted nature.
  • 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: Mr. Woodcock
Triple: [Craig Gillespie, directed, Mr. Woodcock]
Generated description
Mr. Woodcock is a 2007 American comedy film about a man who discovers that his overbearing former gym teacher is engaged to his mother.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mr. Woodcock
Target entity description: Mr. Woodcock is a 2007 American comedy film about a man who discovers that his overbearing former gym teacher is engaged to his mother.
  • A. Mr. Jones
    "Mr. Jones" is a hit alternative rock song by Counting Crows, known for its introspective lyrics about fame, dreams, and identity.
  • B. Mr. Brown
    Mr. Brown is the kind-hearted but often flustered father figure from the "Paddington" film series.
  • C. Mr. Sparks
    Mr. Sparks is a friendly, mechanically skilled character in the Noddy children's stories who often helps fix things in Toyland.
  • D. Mr. Skeffington
    Mr. Skeffington is a 1944 drama film starring Bette Davis, known for its exploration of vanity, marriage, and personal transformation.
  • E. Mr. Harling
    Mr. Harling is a prosperous, energetic merchant and the head of the Harling family in Willa Cather’s novel "My Ántonia," known for his strict yet fundamentally kind-hearted nature.
  • 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_69bd4464ba3c8190bc16b2ebbe42ddb0 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a928dfc8190971a9e28d5c10446 completed March 20, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefe325988190b35e3502f147c9c2 completed March 21, 2026, 7:22 p.m.
NEDg Description generation batch_69bef0b2b6448190be1c465738be741b completed March 21, 2026, 7:25 p.m.
NED2 Entity disambiguation (via description) batch_69bef121817c8190aebd27ee34c0a419 completed March 21, 2026, 7:27 p.m.
Created at: March 20, 2026, 1:47 p.m.