Triple

T22436444
Position Surface form Disambiguated ID Type / Status
Subject Carla E554635 entity
Predicate closeFriendOf P8712 FINISHED
Object Vanessa NE NERFINISHED

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: Vanessa | Statement: [Carla, closeFriendOf, Vanessa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vanessa
Context triple: [Carla, closeFriendOf, Vanessa]
  • A. Vanessa
    Vanessa is the enigmatic, emotionally complex woman at the center of the film "By the Sea," whose inner turmoil drives the story’s exploration of marriage and personal grief.
  • B. Vanessa
    Vanessa is a fictional character associated with the setting of a beauty shop, likely depicted as someone involved in or frequenting the salon environment.
  • C. Vanessa
    Vanessa is a central character in the musical and film "In the Heights," portrayed as an ambitious young woman striving to leave her Washington Heights neighborhood for a better life.
  • D. Vanessa
    Vanessa is a fictional member of the De la Vega family, often depicted within stories involving heritage, drama, and romance.
  • E. Vanessa
    Vanessa is a central character in the sitcom "Grandfathered," known for her close connection to the protagonist and involvement in the show's family-centered storylines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

Provenance (2 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_69e11e5010e48190ae1e9c9db9697637 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ade60508190b0100d5c2843b920 completed April 29, 2026, 1:11 a.m.
Created at: April 16, 2026, 8:47 p.m.