Triple

T13241649
Position Surface form Disambiguated ID Type / Status
Subject Mennekes E315293 entity
Predicate brand P1500 FINISHED
Object MENNEKES E315293 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: MENNEKES | Statement: [Mennekes, brand, MENNEKES]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MENNEKES
Context triple: [Mennekes, brand, MENNEKES]
  • A. Mennekes chosen
    Mennekes is a German electrical engineering company best known in e-mobility for developing the widely adopted Type 2 AC charging connector for electric vehicles.
  • B. Wittmann
    Wittmann is a German surname borne by various notable individuals across fields such as military history, sports, and academia.
  • C. Menzel
    Menzel is a locality or district that forms part of the town of Rüthen in North Rhine-Westphalia, Germany.
  • D. Menzel
    Menzel is the surname of Idina Menzel, the American actress and singer best known for her roles in Broadway musicals and the film "Frozen."
  • E. Werneck
    Werneck is a market town in the Schweinfurt district of northern Bavaria, Germany, known for its baroque palace and surrounding rural landscape.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d59e84c8190a9e547d0fe26a5f9 completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff3438888190b4aecb0b67153ed9 completed May 3, 2026, 7:54 a.m.
Created at: April 9, 2026, 9:23 p.m.