Triple

T16146237
Position Surface form Disambiguated ID Type / Status
Subject Mary Ludwig Hays E391788 entity
Predicate hasFamilyName 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: [Mary Ludwig Hays, hasFamilyName, Hays]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hays
Context triple: [Mary Ludwig Hays, hasFamilyName, 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. Hays, Texas
    Hays, Texas is a small unincorporated community located within Hays County in central Texas.
  • D. Haysville, Kansas
    Haysville, Kansas is a small suburban city within the Wichita metropolitan area known for its residential character and community-focused atmosphere.
  • E. Hutchinson
    Hutchinson is a common English surname borne by numerous notable individuals across fields such as science, politics, and the arts.
  • 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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21d9376fc8190bd9ef586b00c1d3b completed April 17, 2026, 11:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7a59c0481908eb346efaf10a0f6 completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:01 a.m.