Triple

T3052863
Position Surface form Disambiguated ID Type / Status
Subject Peanuts E60410 entity
Predicate influenced P9 FINISHED
Object Garfield E313363 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: Garfield | Statement: [Peanuts, influenced, Garfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garfield
Context triple: [Peanuts, influenced, Garfield]
  • A. Garfield
    Garfield is best known as the 20th president of the United States, whose term in 1881 was cut short by assassination.
  • B. Garfield chosen
    Garfield is a famous orange comic-strip cat created by Jim Davis, known for his laziness, love of lasagna, and sarcastic attitude.
  • C. Magilla Gorilla
    Magilla Gorilla is a classic Hanna-Barbera animated television character, a lovable but trouble-prone gorilla often featured in comedic situations involving his attempts to find a permanent home.
  • D. Krusty the Clown
    Krusty the Clown is a cynical, hard-living television clown and recurring character from the animated series "The Simpsons."
  • E. Taz
    Taz is a major 17th-century halachic commentary on the Shulchan Aruch, authored by Rabbi David HaLevi Segal and highly influential in later Jewish legal works.
  • 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_69ad8578137c81908259dcb27c7d6d7c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9bf3c52c8190bbe8e5cb98c21715 completed March 8, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1eefd3860819085cefea633b5dca9 completed March 11, 2026, 10:38 p.m.
Created at: March 8, 2026, 3:01 p.m.