Triple

T17292156
Position Surface form Disambiguated ID Type / Status
Subject Randall Poster E419809 entity
Predicate notableWork P4 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: [Randall Poster, notableWork, Carol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carol
Context triple: [Randall Poster, notableWork, 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 central character in the meta-horror comedy film "The Final Girls," portrayed as a sweet but archetypal 1980s slasher-movie camp counselor who becomes crucial to the story’s emotional core.
  • 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_69d886db32608190a61e18862c5a8af6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e4378438508190924f732ad748b4d0 completed April 19, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a017959ffb0819099d70ed1541158ee completed May 11, 2026, 6:38 a.m.
Created at: April 10, 2026, 5:40 a.m.