Triple

T5233909
Position Surface form Disambiguated ID Type / Status
Subject Arthur Garfield Hays E118173 entity
Predicate familyName P18 FINISHED
Object Hays E292329 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: Hays | Statement: [Arthur Garfield Hays, familyName, Hays]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hays
Context triple: [Arthur Garfield Hays, familyName, Hays]
  • A. Hays chosen
    Hays is a surname most notably associated with Will H. Hays, the American politician and film industry figure behind the early Hollywood production code.
  • B. Hays, Kansas
    Hays, Kansas is a regional city in northwestern Kansas known as a commercial, educational, and medical hub, home to Fort Hays State University and rich frontier history.
  • C. Hutchinson
    Hutchinson is a common English surname borne by numerous notable individuals across fields such as science, politics, and the arts.
  • D. Hutchinson
    Hutchinson is a long-established British publishing house known for producing a wide range of fiction and non-fiction titles.
  • E. سيبويه
    سيبويه هو نحوي ولغوي بصري من القرن الثاني الهجري يُعد من أبرز أئمة النحو العربي ومؤلف كتاب "الكتاب" الذي يُعد من أهم المراجع في النحو واللغة.
  • 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_69bd4466fb8c819083b806a79414d7e4 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b04c03481908d901788ce2c4128 completed March 20, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef818f31c8190a26950dcd9d6a895 completed March 21, 2026, 7:57 p.m.
Created at: March 20, 2026, 1:49 p.m.