Triple

T9999865
Position Surface form Disambiguated ID Type / Status
Subject Louis Ozawa Changchien E197296 entity
Predicate notableWork P4 FINISHED
Object Predators E417486 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: Predators | Statement: [Louis Ozawa Changchien, notableWork, Predators]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Predators
Context triple: [Louis Ozawa Changchien, notableWork, Predators]
  • A. Predators (2010 film) chosen
    Predators (2010 film) is a science fiction action movie in the Predator franchise that follows a group of elite warriors hunted on an alien planet by advanced extraterrestrial predators.
  • B. Predator
    Predator is Acer’s gaming-focused brand known for its high-performance laptops, desktops, and accessories designed for enthusiast and professional gamers.
  • C. Predator
    Predator is a 1987 science fiction action film in which an elite military team in a Central American jungle is hunted by a technologically advanced alien warrior.
  • D. The Predator
    The Predator is a 2018 science fiction action film that continues the iconic Predator franchise with a modern, humor-tinged take on humans battling lethal alien hunters.
  • E. Hunters
    Hunters is a residential neighborhood located within the Kasarani area of Nairobi, Kenya.
  • 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_69ca82f3b61c81908ecc2c1c96dbc2e4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdcc8dc9c081909b6d20909ada09cf completed April 2, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69d26a36aadc81909978b71bdb3a6654 completed April 5, 2026, 1:57 p.m.
Created at: March 30, 2026, 8:51 p.m.