Triple

T13006160
Position Surface form Disambiguated ID Type / Status
Subject John Magaro E322291 entity
Predicate appearedIn P795 FINISHED
Object Carol E307551 NE FINISHED

How this triple was built (2 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: [John Magaro, appearedIn, Carol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carol
Context triple: [John Magaro, appearedIn, 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 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.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9b27ec8190815c40a05b9ba7d0 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbc5c9a88190b70bda472bf3b062 completed May 3, 2026, 4:15 a.m.
Created at: April 9, 2026, 8:48 p.m.