Triple

T10616485
Position Surface form Disambiguated ID Type / Status
Subject Alvan C. Gillem E276133 entity
Predicate familyName P18 FINISHED
Object Gillem
Gillem is a surname most notably associated with Alvan C. Gillem, a United States Army officer who served during the American Civil War.
 E876045 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: Gillem | Statement: [Alvan C. Gillem, familyName, Gillem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gillem
Context triple: [Alvan C. Gillem, familyName, Gillem]
  • A. Guillem
    Guillem is a central character in Isabel Allende’s novel "A Long Petal of the Sea," a young idealistic fighter in the Spanish Civil War whose fate shapes the story’s exploration of exile, love, and resilience.
  • B. Baltasar
    Baltasar is a variant of the name Belshazzar, historically associated with the last king of Babylon mentioned in the biblical Book of Daniel.
  • C. Guillermo
    Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
  • D. Blasco
    Blasco is a masculine given name of Spanish origin, historically borne by notable figures such as colonial administrators and writers.
  • E. Ferrera
    Ferrera is a Spanish-origin surname most prominently associated with American actress and producer America Ferrera.
  • 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: Gillem
Triple: [Alvan C. Gillem, familyName, Gillem]
Generated description
Gillem is a surname most notably associated with Alvan C. Gillem, a United States Army officer who served during the American Civil War.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gillem
Target entity description: Gillem is a surname most notably associated with Alvan C. Gillem, a United States Army officer who served during the American Civil War.
  • A. Guillem
    Guillem is a central character in Isabel Allende’s novel "A Long Petal of the Sea," a young idealistic fighter in the Spanish Civil War whose fate shapes the story’s exploration of exile, love, and resilience.
  • B. Baltasar
    Baltasar is a variant of the name Belshazzar, historically associated with the last king of Babylon mentioned in the biblical Book of Daniel.
  • C. Guillermo
    Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
  • D. Blasco
    Blasco is a masculine given name of Spanish origin, historically borne by notable figures such as colonial administrators and writers.
  • E. Ferrera
    Ferrera is a Spanish-origin surname most prominently associated with American actress and producer America Ferrera.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df6d76dc8190bd8d481fed3225d9 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96b7bb7108190b0f1cbe4117abec0 completed April 10, 2026, 9:28 p.m.
NEDg Description generation batch_69d96dee84f48190bf5b0cb1115a8bba completed April 10, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_69d9708824208190acf75933962d690f completed April 10, 2026, 9:50 p.m.
Created at: April 8, 2026, 7:33 p.m.