Triple

T16815278
Position Surface form Disambiguated ID Type / Status
Subject Cheri Steinkellner E408727 entity
Predicate hasChild P369 FINISHED
Object Kit Steinkellner E1234958 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: Kit Steinkellner | Statement: [Cheri Steinkellner, hasChild, Kit Steinkellner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kit Steinkellner
Context triple: [Cheri Steinkellner, hasChild, Kit Steinkellner]
  • A. Kit Steinkellner chosen
    Kit Steinkellner is an American television writer and playwright best known as the creator and showrunner of the drama series "Sorry for Your Loss."
  • B. Markus Sattler
    Markus Sattler is a German software engineer and entrepreneur best known as a co-founder and former CTO of the email marketing platform Mailjet.
  • C. Stephan Sauer
    Stephan Sauer is a notable individual who shares the surname Sauer and is recognized for achievements significant enough to be specifically referenced.
  • D. Stefan Vogl
    Stefan Vogl is an ice hockey player known for emerging from the development system of the German club ESV Kaufbeuren.
  • E. Stefan Grube
    Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b2e0e05081908bd5eaa64abe133d completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb0f863081908e74dc4a7c91e91d completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:23 a.m.