Triple

T19121106
Position Surface form Disambiguated ID Type / Status
Subject Norman Schwab E468046 entity
Predicate hasGivenName P17 FINISHED
Object Norman NE NERFINISHED

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: Norman | Statement: [Norman Schwab, hasGivenName, Norman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norman
Context triple: [Norman Schwab, hasGivenName, Norman]
  • A. Norman
    Norman is a medieval European architectural and cultural style characterized by massive stone construction, rounded arches, and fortress-like buildings introduced by the Normans after the 11th century.
  • B. Norman
    Norman is a city in central Oklahoma known for its strong ties to meteorology and atmospheric research, including hosting major national weather institutions.
  • C. Norman
    The Normans were a medieval people of Viking origin who settled in northern France and became influential conquerors and rulers across Europe and the Mediterranean, notably shaping the culture and politics of regions such as England, southern Italy, and Sicily.
  • D. Norman chosen
    Norman is a masculine given name of English origin that became widely used in the English-speaking world.
  • E. Old Norman
    Old Norman is a medieval Romance language that developed in Normandy from Latin and significantly influenced the vocabulary of English and other regional languages.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e3c921d4819092e2ae237bf85978 completed April 20, 2026, 8:28 a.m.
Created at: April 10, 2026, 12:05 p.m.