Triple

T14840887
Position Surface form Disambiguated ID Type / Status
Subject Chris Kattan E348959 entity
Predicate notableCharacter P1481 FINISHED
Object Mango E1053945 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: Mango | Statement: [Chris Kattan, notableCharacter, Mango]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mango
Context triple: [Chris Kattan, notableCharacter, Mango]
  • A. Mango
    Mango is a sweet, tropical stone fruit widely cultivated and consumed around the world, especially in South Asia.
  • B. MANGO
    MANGO is the callsign of Mango Airlines, a South African low-cost carrier known for its bright orange livery and domestic routes.
  • C. Haden mango
    Haden mango is a historically important and widely grown mango cultivar from Florida known for its rich flavor, vibrant color, and role as a parent to many modern mango varieties.
  • D. The Mango chosen
    "The Mango" is an episode of the television sitcom Seinfeld, known for its storyline involving fruit, sexual performance, and the characters' anxieties about satisfaction.
  • E. Mulgoba mango
    Mulgoba mango is a classic Indian mango cultivar known for its rich flavor and aromatic, fiberless flesh, and for serving as a parent to several important modern mango varieties.
  • 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_69d822ec69008190a9232caa68836872 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded28e40f08190b309d8ac6404d2fc completed April 14, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe38a9eb9481908ca509f484007cf6 completed May 8, 2026, 7:25 p.m.
Created at: April 10, 2026, 1:53 a.m.