Triple

T9759419
Position Surface form Disambiguated ID Type / Status
Subject Lili E236631 entity
Predicate artDirectionBy P7743 FINISHED
Object Paul Groesse
Paul Groesse was an Academy Award–winning Hollywood art director known for his work on classic mid-20th-century films.
E871102 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: Paul Groesse | Statement: [Lili, artDirectionBy, Paul Groesse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Groesse
Context triple: [Lili, artDirectionBy, Paul Groesse]
  • A. Paul Knabenshue
    Paul Knabenshue was an American diplomat best known for serving as the first U.S. Ambassador to Iraq in the early 20th century.
  • B. Michael Schoeffling
    Michael Schoeffling is an American former actor and model best known for his role as Jake Ryan in the 1984 film "Sixteen Candles."
  • C. Eric Pleskow
    Eric Pleskow was an Austrian-born American film executive and producer best known for leading major studios and co-founding the influential independent film company Orion Pictures.
  • D. Michael Holzer
    Michael Holzer is an architect best known as one of the founders of the avant-garde Austrian architecture firm Coop Himmelb(l)au.
  • E. Kevin Nolting
    Kevin Nolting is an American film editor best known for his work on Pixar animated features, including the Academy Award-winning film "Up."
  • 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: Paul Groesse
Triple: [Lili, artDirectionBy, Paul Groesse]
Generated description
Paul Groesse was an Academy Award–winning Hollywood art director known for his work on classic mid-20th-century films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Paul Groesse
Target entity description: Paul Groesse was an Academy Award–winning Hollywood art director known for his work on classic mid-20th-century films.
  • A. Paul Knabenshue
    Paul Knabenshue was an American diplomat best known for serving as the first U.S. Ambassador to Iraq in the early 20th century.
  • B. Michael Schoeffling
    Michael Schoeffling is an American former actor and model best known for his role as Jake Ryan in the 1984 film "Sixteen Candles."
  • C. Eric Pleskow
    Eric Pleskow was an Austrian-born American film executive and producer best known for leading major studios and co-founding the influential independent film company Orion Pictures.
  • D. Michael Holzer
    Michael Holzer is an architect best known as one of the founders of the avant-garde Austrian architecture firm Coop Himmelb(l)au.
  • E. Kevin Nolting
    Kevin Nolting is an American film editor best known for his work on Pixar animated features, including the Academy Award-winning film "Up."
  • 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_69ca84d64f6c8190a4ed4e9f5936eda5 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda049995c81908569ec61805642b2 completed April 1, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9330fa33c8190b507ad18362a6c64 completed April 10, 2026, 5:27 p.m.
NEDg Description generation batch_69d93802a4488190aa86ae209650d4e7 completed April 10, 2026, 5:48 p.m.
NED2 Entity disambiguation (via description) batch_69d938fcc3c48190a4acaaf75c1aa304 completed April 10, 2026, 5:53 p.m.
Created at: March 30, 2026, 8:24 p.m.