Triple

T12588758
Position Surface form Disambiguated ID Type / Status
Subject Frank Seiberling E300541 entity
Predicate familyName P18 FINISHED
Object Seiberling
Seiberling is a surname most notably associated with American industrialist Frank Seiberling, co-founder of the Goodyear Tire & Rubber Company.
 E993295 NE FINISHED

How this triple was built (4 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: Seiberling | Statement: [Frank Seiberling, familyName, Seiberling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Seiberling
Context triple: [Frank Seiberling, familyName, Seiberling]
  • A. Trumbauer
    Trumbauer is a surname most notably associated with American architect Horace Trumbauer, known for his grand Gilded Age mansions and institutional buildings.
  • B. Kleiser
    Kleiser is a surname most notably associated with American film director Randal Kleiser, known for directing the musical romantic comedy "Grease."
  • C. Gallaher
    Gallaher is a surname of Irish origin borne by various notable individuals, including figures in sports, politics, and the arts.
  • D. Spreckels
    Spreckels is a prominent American family name historically associated with major sugar industry enterprises and philanthropy, particularly in California.
  • E. Swasey
    Swasey is a surname of English origin borne by various notable individuals, including architects, politicians, and academics.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Seiberling
Triple: [Frank Seiberling, familyName, Seiberling]
Generated description
Seiberling is a surname most notably associated with American industrialist Frank Seiberling, co-founder of the Goodyear Tire & Rubber Company.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Seiberling
Target entity description: Seiberling is a surname most notably associated with American industrialist Frank Seiberling, co-founder of the Goodyear Tire & Rubber Company.
  • A. Trumbauer
    Trumbauer is a surname most notably associated with American architect Horace Trumbauer, known for his grand Gilded Age mansions and institutional buildings.
  • B. Kleiser
    Kleiser is a surname most notably associated with American film director Randal Kleiser, known for directing the musical romantic comedy "Grease."
  • C. Gallaher
    Gallaher is a surname of Irish origin borne by various notable individuals, including figures in sports, politics, and the arts.
  • D. Spreckels
    Spreckels is a prominent American family name historically associated with major sugar industry enterprises and philanthropy, particularly in California.
  • E. Swasey
    Swasey is a surname of English origin borne by various notable individuals, including architects, politicians, and academics.
  • F. None of above. chosen

Provenance (5 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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954bd5e8c8190a2f233b91682341f completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ec0a60c8190948706e8b2fcc0ad completed May 2, 2026, 8:29 p.m.
NEDg Description generation batch_69f662cc2a208190870e2099a8bb5d04 completed May 2, 2026, 8:47 p.m.
NED2 Entity disambiguation (via description) batch_69f6638319d48190ba73480ce6e91d83 completed May 2, 2026, 8:50 p.m.
Created at: April 9, 2026, 5:06 p.m.