Triple

T5532762
Position Surface form Disambiguated ID Type / Status
Subject Gran Torino E145087 entity
Predicate screenwriter P2831 FINISHED
Object Nick Schenk
Nick Schenk is an American screenwriter best known for writing the Clint Eastwood film "Gran Torino."
 E529155 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: Nick Schenk | Statement: [Gran Torino, screenwriter, Nick Schenk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nick Schenk
Context triple: [Gran Torino, screenwriter, Nick Schenk]
  • A. Dick Schoof
    Dick Schoof is a Dutch civil servant and politician who has served as Prime Minister of the Netherlands.
  • B. Tom Schaul
    Tom Schaul is a machine learning researcher known for his contributions to deep reinforcement learning, including co-developing the Dueling DQN architecture.
  • C. John Schehr
    John Schehr was a German communist politician and anti-fascist resistance figure who briefly led the Communist Party of Germany before being killed by the Nazis in 1934.
  • D. Eric Wetzels
    Eric Wetzels is a Dutch politician who serves as the chairperson of the People's Party for Freedom and Democracy (VVD).
  • E. Ben Schnetzer
    Ben Schnetzer is an American actor known for his roles in films such as "Pride," "The Book Thief," and the fantasy epic "Warcraft."
  • 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: Nick Schenk
Triple: [Gran Torino, screenwriter, Nick Schenk]
Generated description
Nick Schenk is an American screenwriter best known for writing the Clint Eastwood film "Gran Torino."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nick Schenk
Target entity description: Nick Schenk is an American screenwriter best known for writing the Clint Eastwood film "Gran Torino."
  • A. Dick Schoof
    Dick Schoof is a Dutch civil servant and politician who has served as Prime Minister of the Netherlands.
  • B. Tom Schaul
    Tom Schaul is a machine learning researcher known for his contributions to deep reinforcement learning, including co-developing the Dueling DQN architecture.
  • C. John Schehr
    John Schehr was a German communist politician and anti-fascist resistance figure who briefly led the Communist Party of Germany before being killed by the Nazis in 1934.
  • D. Eric Wetzels
    Eric Wetzels is a Dutch politician who serves as the chairperson of the People's Party for Freedom and Democracy (VVD).
  • E. Ben Schnetzer
    Ben Schnetzer is an American actor known for his roles in films such as "Pride," "The Book Thief," and the fantasy epic "Warcraft."
  • 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_69c008f9955881909bfa8348b56b4739 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f9ea2c88190a68642f5799bd8ff completed March 22, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c028094fa48190a1f48779a7963af9 completed March 22, 2026, 5:34 p.m.
NEDg Description generation batch_69c033ddc7148190ba64ebfc2472c367 completed March 22, 2026, 6:24 p.m.
NED2 Entity disambiguation (via description) batch_69c036725fc481908ab0e260892d8243 completed March 22, 2026, 6:35 p.m.
Created at: March 22, 2026, 3:34 p.m.