Triple

T8412324
Position Surface form Disambiguated ID Type / Status
Subject Tammy Blanchard E198653 entity
Predicate notableWork P4 FINISHED
Object Bella
Bella is a 2006 independent drama film starring Tammy Blanchard that explores themes of love, redemption, and unexpected family.
E732795 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: Bella | Statement: [Tammy Blanchard, notableWork, Bella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bella
Context triple: [Tammy Blanchard, notableWork, Bella]
  • A. Bella
    Bella is the main human protagonist of the Twilight series, known for her introspective nature and complex relationship with the supernatural world.
  • B. Bella Greene
    Bella Greene is a relatively obscure individual whose specific public achievements or background are not widely documented.
  • C. Esme
    Esme is a song by Joanna Newsom from her 2010 album "Have One on Me," noted for its intricate harp arrangements and poetic lyrics.
  • D. Tessa
    Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
  • E. Rosalie
    "Rosalie" is a popular song by composer Cole Porter, featured in the Ella Fitzgerald album "Ella Fitzgerald Sings the Cole Porter Song Book."
  • 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: Bella
Triple: [Tammy Blanchard, notableWork, Bella]
Generated description
Bella is a 2006 independent drama film starring Tammy Blanchard that explores themes of love, redemption, and unexpected family.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bella
Target entity description: Bella is a 2006 independent drama film starring Tammy Blanchard that explores themes of love, redemption, and unexpected family.
  • A. Bella
    Bella is the main human protagonist of the Twilight series, known for her introspective nature and complex relationship with the supernatural world.
  • B. Bella Greene
    Bella Greene is a relatively obscure individual whose specific public achievements or background are not widely documented.
  • C. Esme
    Esme is a song by Joanna Newsom from her 2010 album "Have One on Me," noted for its intricate harp arrangements and poetic lyrics.
  • D. Tessa
    Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
  • E. Rosalie
    Rosalie is a musical comedy best known for its Broadway production featuring music by George Gershwin and Sigmund Romberg.
  • 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_69ca831201b481909e137936ef99ff11 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb83e0341c819080506e696131671e completed March 31, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce0322d1448190aceaf7486c110ff7 completed April 2, 2026, 5:48 a.m.
NEDg Description generation batch_69ce0781859c8190bb92f41c00af459b completed April 2, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_69ce089d09c08190ba321aed4044a862 completed April 2, 2026, 6:11 a.m.
Created at: March 30, 2026, 6:05 p.m.