Triple

T10738488
Position Surface form Disambiguated ID Type / Status
Subject Heike Makatsch E253256 entity
Predicate hasFamilyName P18 FINISHED
Object Makatsch E253256 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: Makatsch | Statement: [Heike Makatsch, hasFamilyName, Makatsch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makatsch
Context triple: [Heike Makatsch, hasFamilyName, Makatsch]
  • A. Makatsch chosen
    Makatsch is the surname of German actress and television presenter Heike Makatsch, known for her roles in films such as "Love Actually" and "Resident Evil."
  • B. Makadara
    Makadara is a residential and commercial neighborhood in Nairobi, Kenya, known for its dense population, vibrant local markets, and mix of low- to middle-income housing.
  • C. Marcali
    Marcali is a small town in southwestern Hungary known for its agricultural surroundings and role as a local administrative and service center in Somogy County.
  • D. Maklak
    Maklak is the self-designated name (autonym) used by the Modoc people to refer to themselves.
  • E. Matabaan
    Matabaan is a town in central Somalia that serves as one of the urban centers within the federal member state of Hirshabelle.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d710424d8c81908ee9b59d622f2af5 completed April 9, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69de84932abc8190907c32720e35442e completed April 14, 2026, 6:16 p.m.
Created at: April 8, 2026, 9:14 p.m.