Triple

T5831004
Position Surface form Disambiguated ID Type / Status
Subject Affonso Gonçalves E129343 entity
Predicate edited P1932 FINISHED
Object Carol
Carol is a 2015 romantic drama film directed by Todd Haynes, acclaimed for its nuanced portrayal of a same-sex relationship in 1950s America and its elegant, atmospheric style.
 E307551 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: Carol | Statement: [Affonso Gonçalves, edited, Carol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Carol
Context triple: [Affonso Gonçalves, edited, Carol]
  • A. Carol
    Carol is a feminine given name commonly used in English-speaking countries, often associated with figures in entertainment and literature.
  • B. Carol
    Carol is a critically acclaimed 2015 romantic drama film, directed by Todd Haynes and starring Cate Blanchett and Rooney Mara, about a forbidden love affair between two women in 1950s New York.
  • C. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • D. Barbara
    Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
  • E. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • 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: Carol
Triple: [Affonso Gonçalves, edited, Carol]
Generated description
Carol is a 2015 romantic drama film directed by Todd Haynes, acclaimed for its nuanced portrayal of a same-sex relationship in 1950s America and its elegant, atmospheric style.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Carol
Target entity description: Carol is a 2015 romantic drama film directed by Todd Haynes, acclaimed for its nuanced portrayal of a same-sex relationship in 1950s America and its elegant, atmospheric style.
  • A. Carol
    Carol is a feminine given name commonly used in English-speaking countries, often associated with figures in entertainment and literature.
  • B. Carol chosen
    Carol is a critically acclaimed 2015 romantic drama film, directed by Todd Haynes and starring Cate Blanchett and Rooney Mara, about a forbidden love affair between two women in 1950s New York.
  • C. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • D. Barbara
    Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
  • E. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • F. None of above.

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_69c00849d55481908b4f9f5543e0bf6d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0346ac31c8190bbd28444f75da875 completed March 22, 2026, 6:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a18c48588190b4848dff1c277079 completed March 23, 2026, 2:12 a.m.
NEDg Description generation batch_69c0a33036bc8190b7c0b453a1d8f319 completed March 23, 2026, 2:19 a.m.
NED2 Entity disambiguation (via description) batch_69c0a38522f0819085514ae6f41c5991 completed March 23, 2026, 2:20 a.m.
Created at: March 22, 2026, 3:54 p.m.