Triple

T1448876
Position Surface form Disambiguated ID Type / Status
Subject Marcus König E31240 entity
Predicate hasGivenName P17 FINISHED
Object Marcus E70882 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: Marcus | Statement: [Marcus König, hasGivenName, Marcus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marcus
Context triple: [Marcus König, hasGivenName, Marcus]
  • A. Marcus chosen
    Marcus is a masculine given name of ancient Roman origin that has been widely used across many cultures and historical periods.
  • B. Marco
    Marco is a central character in Arthur Miller’s play "A View from the Bridge," depicted as a hardworking Italian immigrant whose fierce sense of family loyalty and justice drives much of the drama’s conflict.
  • C. Marc
    Marc is the given name of Marc Andreessen, the influential American entrepreneur, software engineer, and venture capitalist known for co-creating the Mosaic web browser and co-founding Netscape and Andreessen Horowitz.
  • D. Maccus
    Maccus is an Old Norse–derived given name that served as the historical root for the later surname and given name Maxwell.
  • E. Martin
    Martin is a minor but kind-hearted character in Ernest Hemingway's novella "The Old Man and the Sea," known for helping the old fisherman Santiago.
  • 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_69a499171a28819085b993a3ac78e363 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c55c408c8190917ed44d9070a2fb completed March 1, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08c229808190af9936b481390170 completed March 8, 2026, 5:27 a.m.
Created at: March 1, 2026, 8 p.m.