Triple

T12472645
Position Surface form Disambiguated ID Type / Status
Subject Todd Muller E298098 entity
Predicate familyName P18 FINISHED
Object Muller E35404 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: Muller | Statement: [Todd Muller, familyName, Muller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muller
Context triple: [Todd Muller, familyName, Muller]
  • A. Müller chosen
    Müller is a common German surname, equivalent to "Miller" in English, historically associated with the occupation of operating a mill.
  • B. Millerand
    Millerand is a French surname most notably associated with Alexandre Millerand, a prominent early 20th-century French statesman and President of France.
  • C. Meyer-Hetling
    Meyer-Hetling is a German surname most notably associated with Konrad Meyer-Hetling, an agronomist and SS officer involved in Nazi settlement planning.
  • D. Millner
    Millner is an English occupational surname historically associated with people who made or sold hats or millinery goods.
  • E. Maufe
    Maufe is a surname most notably associated with Sir Edward Maufe, a 20th-century British architect known for designing Guildford Cathedral and several prominent war memorials.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dca022c819082138fd4d08516da completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f2373308190b41aafa635c8de5e completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:56 p.m.