Triple

T2436671
Position Surface form Disambiguated ID Type / Status
Subject Roman Polanski E52976 entity
Predicate notableWork P4 FINISHED
Object Tess
Tess is a 1979 period drama film directed by Roman Polanski, adapted from Thomas Hardy’s novel "Tess of the d'Urbervilles."
 E265925 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: Tess | Statement: [Roman Polanski, notableWork, Tess]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tess
Context triple: [Roman Polanski, notableWork, Tess]
  • A. Tess
    Tess is a central character in the musical film "Burlesque," serving as the tough but caring owner and manager of the struggling burlesque club.
  • B. The Farmer’s Daughter
    The Farmer’s Daughter is a 1947 American romantic comedy film starring Loretta Young as a Swedish-American farm girl who becomes involved in politics.
  • C. Adam Bede
    Adam Bede is a 1859 realist novel by George Eliot that portrays rural English life and moral dilemmas through the story of a principled carpenter and those around him.
  • D. Bathsheba
    Bathsheba is a prominent biblical figure known as the wife of King David and the mother of King Solomon.
  • E. Silas Marner
    Silas Marner is a novel by George Eliot that tells the story of a reclusive weaver whose life is transformed by the arrival of an orphaned child.
  • 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: Tess
Triple: [Roman Polanski, notableWork, Tess]
Generated description
Tess is a 1979 period drama film directed by Roman Polanski, adapted from Thomas Hardy’s novel "Tess of the d'Urbervilles."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tess
Target entity description: Tess is a 1979 period drama film directed by Roman Polanski, adapted from Thomas Hardy’s novel "Tess of the d'Urbervilles."
  • A. Tess
    Tess is a central character in the musical film "Burlesque," serving as the tough but caring owner and manager of the struggling burlesque club.
  • B. The Farmer’s Daughter
    The Farmer’s Daughter is a 1947 American romantic comedy film starring Loretta Young as a Swedish-American farm girl who becomes involved in politics.
  • C. Adam Bede
    Adam Bede is a 1859 realist novel by George Eliot that portrays rural English life and moral dilemmas through the story of a principled carpenter and those around him.
  • D. Bathsheba
    Bathsheba is a prominent biblical figure known as the wife of King David and the mother of King Solomon.
  • E. Silas Marner
    Silas Marner is a novel by George Eliot that tells the story of a reclusive weaver whose life is transformed by the arrival of an orphaned child.
  • 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9f342e88190a430b02842ded418 completed March 7, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf7085b88190938c4eefa4380970 completed March 9, 2026, 12:39 p.m.
NEDg Description generation batch_69aec30189d081908bb6865937aff20d completed March 9, 2026, 12:54 p.m.
NED2 Entity disambiguation (via description) batch_69aec39bb6a4819084652814e18f60d4 completed March 9, 2026, 12:56 p.m.
Created at: March 6, 2026, 9:43 p.m.