Triple

T15439142
Position Surface form Disambiguated ID Type / Status
Subject Graham Spanier E369851 entity
Predicate familyName P18 FINISHED
Object Spanier
Spanier is a surname most prominently associated with Graham Spanier, the former president of Pennsylvania State University.
E1158036 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: Spanier | Statement: [Graham Spanier, familyName, Spanier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spanier
Context triple: [Graham Spanier, familyName, Spanier]
  • A. Gallego
    Gallego is a Spanish surname commonly associated with people of Galician origin or ancestry.
  • B. Bourbon Spain
    Bourbon Spain was the early 18th-century Spanish monarchy under the French-origin Bourbon dynasty, marked by centralizing reforms and involvement in the War of the Spanish Succession.
  • C. Spangenberg
    Spangenberg is a small town in Germany, historically situated within the region of Westphalia.
  • D. Spínola
    Spínola is a Portuguese surname most prominently associated with António de Spínola, a key military figure and political leader during Portugal’s Carnation Revolution.
  • E. Parlatino
    Parlatino is a regional parliamentary organization that brings together the legislative bodies of Latin American countries to promote political integration, democracy, and cooperation across the region.
  • 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: Spanier
Triple: [Graham Spanier, familyName, Spanier]
Generated description
Spanier is a surname most prominently associated with Graham Spanier, the former president of Pennsylvania State University.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Spanier
Target entity description: Spanier is a surname most prominently associated with Graham Spanier, the former president of Pennsylvania State University.
  • A. Gallego
    Gallego is a Spanish surname commonly associated with people of Galician origin or ancestry.
  • B. Bourbon Spain
    Bourbon Spain was the early 18th-century Spanish monarchy under the French-origin Bourbon dynasty, marked by centralizing reforms and involvement in the War of the Spanish Succession.
  • C. Spangenberg
    Spangenberg is a small town in Germany, historically situated within the region of Westphalia.
  • D. Spínola
    Spínola is a Portuguese surname most prominently associated with António de Spínola, a key military figure and political leader during Portugal’s Carnation Revolution.
  • E. Parlatino
    Parlatino is a regional parliamentary organization that brings together the legislative bodies of Latin American countries to promote political integration, democracy, and cooperation across the region.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03eddf258819082679970b7d2b6af completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21a7d44481909a26b5cc331a3259 completed May 9, 2026, 11:59 a.m.
NEDg Description generation batch_69ff23348a448190a2a2953a18b29aaf completed May 9, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_69ff240af68c8190af88834d97a42afb completed May 9, 2026, 12:09 p.m.
Created at: April 10, 2026, 3:21 a.m.