Triple

T15911866
Position Surface form Disambiguated ID Type / Status
Subject Αμυτις E385867 entity
Predicate region P40 FINISHED
Object Media E332060 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: Media | Statement: [Αμυτις, region, Media]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Media
Context triple: [Αμυτις, region, Media]
  • A. Media chosen
    Media was an ancient Iranian kingdom in northwestern Iran, historically ruled by the Medes and known for its role as a major Near Eastern power before being absorbed by the Achaemenid Persian Empire.
  • B. Media
    Media is a small borough in Delaware County, Pennsylvania, that serves as the county seat and is known for its historic downtown and community-oriented character.
  • C. Media Ventures
    Media Ventures is a film and television music production company and composers’ collective founded by Hans Zimmer, known for creating scores for major Hollywood productions.
  • D. MediaCom
    MediaCom is a global media planning and buying agency known for managing advertising and communications strategies for major brands worldwide.
  • E. Media Factory
    Media Factory is a creative and digital media hub at the University of Central Lancashire that provides specialized facilities and resources for media, arts, and design students and professionals.
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1565f621c8190a52cda28237610e8 completed April 16, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5a5b0dc81909606d667c3bc0edf completed May 9, 2026, 10:31 p.m.
Created at: April 10, 2026, 4:52 a.m.