Triple

T10405295
Position Surface form Disambiguated ID Type / Status
Subject Mrs. Potts E245246 entity
Predicate friendOf P8712 FINISHED
Object Cogsworth E668465 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: Cogsworth | Statement: [Mrs. Potts, friendOf, Cogsworth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cogsworth
Context triple: [Mrs. Potts, friendOf, Cogsworth]
  • A. Cogsworth chosen
    Cogsworth is the pompous yet endearing enchanted mantel clock who serves as the Beast’s strict but loyal majordomo in Disney’s Beauty and the Beast.
  • B. Hoggle
    Hoggle is a gruff yet ultimately loyal dwarf-like creature from the fantasy film "Labyrinth," who helps guide the protagonist through the maze.
  • C. Gaston
    Gaston is a masculine given name of French origin commonly used in Francophone countries and beyond.
  • D. Edgar Frog
    Edgar Frog is a comic-book-obsessed teenage vampire hunter from the horror-comedy film "The Lost Boys," known for his dead-serious attitude and monster-fighting expertise.
  • E. Douzy
    Douzy is a small commune in the Ardennes department of northern France, known for its rural character and cross-border ties, including a town twinning with Kaiserslautern in Germany.
  • 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_69d381be340c8190b05998703d42d224 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9e78008819088f0ffba78471509 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fbe721b48190a4fd0c1d839c580e completed April 9, 2026, 7:20 p.m.
Created at: April 6, 2026, 12:08 p.m.