Triple

T14534497
Position Surface form Disambiguated ID Type / Status
Subject Russell E341003 entity
Predicate associatedWith P37 FINISHED
Object Fat Albert E340999 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: Fat Albert | Statement: [Russell, associatedWith, Fat Albert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fat Albert
Context triple: [Russell, associatedWith, Fat Albert]
  • A. Fat Albert chosen
    Fat Albert is a lovable, wisecracking, and overweight African-American teenager who leads a group of urban kids in the animated television series "Fat Albert and the Cosby Kids."
  • B. Fat Albert
    Fat Albert is the nickname of the U.S. Navy Blue Angels’ support transport aircraft, a C-130 Hercules used for logistics and demonstration support.
  • C. Alf
    Alf is the nickname of Allan Langer, a celebrated Australian rugby league halfback renowned for his playmaking skills and success with the Brisbane Broncos and Queensland Maroons.
  • D. Alf
    Alf is a masculine given name, often used in Scandinavian and Germanic countries, typically as a short form of names like Alfred.
  • E. Muttley
    Muttley is a cartoon dog best known as Dick Dastardly’s snickering sidekick in Hanna-Barbera’s slapstick racing and aviation-themed series.
  • 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_69d822dac79c8190a84a073f3cbaced5 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb1b9d39881908c7a3a5b17d432af completed April 14, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde16666b8819090fb33c71515ab0a completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:22 a.m.