Triple

T20521579
Position Surface form Disambiguated ID Type / Status
Subject Donald Keyhoe E503820 entity
Predicate familyName P18 FINISHED
Object Keyhoe
Keyhoe is a surname most notably associated with Donald Keyhoe, an American Marine Corps officer and influential early writer on unidentified flying objects (UFOs).
 E1435191 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: Keyhoe | Statement: [Donald Keyhoe, familyName, Keyhoe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Keyhoe
Context triple: [Donald Keyhoe, familyName, Keyhoe]
  • A. Drieborg
    Drieborg is a small village in the municipality of Oldambt in the province of Groningen in the northeastern Netherlands.
  • B. Kohner
    Kohner is a surname most notably associated with American actress Susan Kohner, known for her acclaimed film and television work in the mid-20th century.
  • C. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • D. Kehler
    Kehler is a German-origin surname borne by various individuals, including American Air Force general C. Robert Kehler.
  • E. Kowen
    Kowen is a locality within the Kowen Forest area near Canberra in the Australian Capital Territory, known for its pine plantations and outdoor recreation activities.
  • 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: Keyhoe
Triple: [Donald Keyhoe, familyName, Keyhoe]
Generated description
Keyhoe is a surname most notably associated with Donald Keyhoe, an American Marine Corps officer and influential early writer on unidentified flying objects (UFOs).
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Keyhoe
Target entity description: Keyhoe is a surname most notably associated with Donald Keyhoe, an American Marine Corps officer and influential early writer on unidentified flying objects (UFOs).
  • A. Drieborg
    Drieborg is a small village in the municipality of Oldambt in the province of Groningen in the northeastern Netherlands.
  • B. Kohner
    Kohner is a surname most notably associated with American actress Susan Kohner, known for her acclaimed film and television work in the mid-20th century.
  • C. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • D. Kehler
    Kehler is a German-origin surname borne by various individuals, including American Air Force general C. Robert Kehler.
  • E. Kowen
    Kowen is a locality within the Kowen Forest area near Canberra in the Australian Capital Territory, known for its pine plantations and outdoor recreation activities.
  • 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_69e0b4b2aa788190ae9eb37c1d73b1f1 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69f46488c819093687b4e07837793 completed April 20, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a089d419ba081909f80b105bb9d9612 completed May 16, 2026, 4:37 p.m.
NEDg Description generation batch_6a089dd1abd08190a662efd4a23eacba completed May 16, 2026, 4:39 p.m.
NED2 Entity disambiguation (via description) batch_6a089e76035c8190b1b48d102f710fdd completed May 16, 2026, 4:42 p.m.
Created at: April 16, 2026, 11:36 a.m.