Triple

T35594629
Position Surface form Disambiguated ID Type / Status
Subject James Ogilvy, 1st Earl of Seafield E1028593 entity
Predicate nobleTitle P914 FINISHED
Object Earl of Seafield
The Earl of Seafield is a Scottish peerage title historically associated with the influential Ogilvy family, prominent in Scottish politics and landownership.
E2225159 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: Earl of Seafield | Statement: [James Ogilvy, 1st Earl of Seafield, nobleTitle, Earl of Seafield]
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: Earl of Seafield
Triple: [James Ogilvy, 1st Earl of Seafield, nobleTitle, Earl of Seafield]
Generated description
The Earl of Seafield is a Scottish peerage title historically associated with the influential Ogilvy family, prominent in Scottish politics and landownership.

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_69f76e0598dc8190a6a093e904b9aa70 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79ea7c15481909d08dedfed3bda02 completed May 3, 2026, 7:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4076d91da88190a12ed4914ae18f5c completed June 28, 2026, 1:20 a.m.
NEDg Description generation batch_6a40776b75bc8190aa748bc0aae9abbf completed June 28, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_6a4077dd15088190a2c22c8e1ca89036 completed June 28, 2026, 1:24 a.m.
Created at: May 3, 2026, 4:05 p.m.