Triple

T18731462
Position Surface form Disambiguated ID Type / Status
Subject Pachinko E458043 entity
Predicate character P662 FINISHED
Object Noa 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: Noa | Statement: [Pachinko, character, Noa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Noa
Context triple: [Pachinko, character, Noa]
  • A. Noa chosen
    Noa is a Hebrew given name commonly used for women in Israel, distinct from the biblical male name Noah.
  • B. Noáin
    Noáin is a municipality in northern Spain’s Navarre region, known for its proximity to Pamplona and its role as a key transport hub with the nearby Pamplona Airport.
  • C. Noe
    Noe is a masculine given name used in various cultures, often as a form of Noah.
  • D. Noora
    Noora is a feminine given name commonly used in Arabic-speaking and other Muslim-majority cultures, often interpreted to mean "light" or "illumination."
  • E. Nassim
    Nassim is the first name of Nassim Nicholas Taleb, a Lebanese-American scholar, statistician, and former trader known for his work on risk, probability, and uncertainty.
  • 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_69d8d393ba9c8190a8b03b04ddbb0a09 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e56d7854748190b66c4aaadfd67f29 completed April 20, 2026, 12:04 a.m.
Created at: April 10, 2026, 11:51 a.m.