Triple

T3067920
Position Surface form Disambiguated ID Type / Status
Subject 127 Hours E62150 entity
Predicate starring P1507 FINISHED
Object Lizzy Caplan E187119 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: Lizzy Caplan | Statement: [127 Hours, starring, Lizzy Caplan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lizzy Caplan
Context triple: [127 Hours, starring, Lizzy Caplan]
  • A. Lizzy Caplan chosen
    Lizzy Caplan is an American actress known for her sharp, often comedic roles in film and television, including standout performances in projects like "Mean Girls," "Masters of Sex," and "Cloverfield."
  • B. Grace Gummer
    Grace Gummer is an American actress known for her work in film, television, and theater, including roles in series like "Mr. Robot" and "The Newsroom."
  • C. Lindsay Applegate
    Lindsay Applegate was a 19th-century American pioneer and trailblazer known for helping establish emigrant routes to the Pacific Northwest.
  • D. Margaret Qualley
    Margaret Qualley is an American actress known for her breakout role in HBO's "The Leftovers" and acclaimed performances in projects like "Maid" and "Once Upon a Time in Hollywood."
  • E. Amber Tamblyn
    Amber Tamblyn is an American actress and writer best known for her roles in the television series "Joan of Arcadia" and films such as "The Sisterhood of the Traveling Pants."
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada0fea06881909e5251eea26599ac completed March 8, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f49ed80819087226b3eaf81965b completed March 12, 2026, 12:56 a.m.
Created at: March 8, 2026, 3:02 p.m.