Triple

T9427425
Position Surface form Disambiguated ID Type / Status
Subject All Too Well: The Short Film E227290 entity
Predicate starring P1507 FINISHED
Object Dylan O’Brien E252468 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: Dylan O’Brien | Statement: [All Too Well: The Short Film, starring, Dylan O’Brien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dylan O’Brien
Context triple: [All Too Well: The Short Film, starring, Dylan O’Brien]
  • A. Dylan O'Brien chosen
    Dylan O'Brien is an American actor best known for starring in the "Maze Runner" film series and the TV show "Teen Wolf."
  • B. Logan Lerman
    Logan Lerman is an American actor best known for his lead role in the "Percy Jackson" film series and performances in movies such as "The Perks of Being a Wallflower" and "Fury."
  • C. Ethan Peck
    Ethan Peck is an American actor best known for portraying Spock in the television series "Star Trek: Strange New Worlds."
  • D. Logan Marshall-Green
    Logan Marshall-Green is an American actor and director known for his roles in films like "Prometheus" and "Upgrade" as well as various television series.
  • E. Tye Sheridan
    Tye Sheridan is an American actor known for roles in films such as Mud, Ready Player One, and the X-Men series, where he portrays the young Cyclops.
  • 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_69ca8436ba308190903e470776d2d893 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7c91ba1c8190b8331fb1ba58cc61 completed April 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1223d3cd8819089fec4c895125049 completed April 4, 2026, 2:37 p.m.
Created at: March 30, 2026, 7:49 p.m.