Triple

T1749035
Position Surface form Disambiguated ID Type / Status
Subject Obsessed E38396 entity
Predicate leadActress P6108 FINISHED
Object Ali Larter E213977 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: Ali Larter | Statement: [Obsessed, leadActress, Ali Larter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ali Larter
Context triple: [Obsessed, leadActress, Ali Larter]
  • A. Ali Larter chosen
    Ali Larter is an American actress and former model best known for her roles in films like "Final Destination" and "Legally Blonde" and the TV series "Heroes."
  • B. Nikki Reed
    Nikki Reed is an American actress and screenwriter best known for her role as Rosalie Hale in the Twilight film series.
  • C. Carla Gugino
    Carla Gugino is an American actress known for her versatile film and television roles, including prominent performances in projects like "Spy Kids," "Sin City," and "The Haunting of Hill House."
  • D. Jorja Fox
    Jorja Fox is an American actress best known for her long-running role as Sara Sidle on the television series CSI: Crime Scene Investigation.
  • E. Erika Christensen
    Erika Christensen is an American actress known for her roles in films like "Traffic" and "Flightplan" and the television series "Parenthood."
  • 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63ee4d2081909dfd6d3244228c56 completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfb98fee88190804f368b484c7305 completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:31 p.m.